Editor’s Choice Articles

In this contribution, a tool developed for the study of the efficiency maps of shifted inductances axes permanent magnet synchronous motors (SIAPMSMs) is presented and made available to the readers. The research builds upon a shared foundation that has already been established in previous works focused on the power capability of synchronous machines. This contribution is an extension of previous works dedicated to the power capabilities of shifted inductances axes synchronous motors where the losses were not considered. In this new contribution, the SIAPMSM models, which include the electromagnetic losses (joule and iron losses), are discussed. The mechanical losses are not included. The classical permanent magnet synchronous machines can be considered a particular case of a SIAPMSM. They will be used to validate the developed tools. The validation study is conducted by comparing the power capabilities and the efficiency maps of SIAPMSMs and classical PMSMs obtained by the newly developed modeling tool and a previously developed modeling tool. Full article

The dual-carbon strategy advocates a green, environmentally friendly, and low-carbon lifestyle. In the field of transportation, electric vehicles (EVs) have been regarded as an effective solution to reduce carbon emissions and to conserve energy. Developing a reasonable charging guidance scheme for users is a feasible way to solve problems, such as the range anxiety of EV users, and has a great application value for the promotion of EVs in the future. In practical situations, how to develop charging induction schemes for users that better meet their needs according to the type of user and their multi-dimensional preferences is the focus of this paper. To this end, this study utilized charging behavioral data to investigate the multi-dimensional charging preference of users based on the collaborative filtering algorithm. Then, a multi-objective optimization model was established based on the preference degree of each charging station and the integrated travel cost. An NSGA-III framework was used to design the algorithm to solve the proposed model. The algorithm was tested using simulation experiments that were designed based on the road network and charging stations in Beijing. The final result is an experimental analysis of the weight matrices for the three different preferences of minimum energy consumption cost, minimum time cost, and minimum fee cost, which yields a difference of about 4.4% between the optimal energy consumption cost and the maximum energy cost, about 2.9% between the optimal time cost and the maximum time cost, and about 10% between the optimal fee cost and the maximum fee cost under these three different preferences, respectively. The proposed multi-objective optimization model is able to provide users with reliable charging station selection by incorporating their personalized charging preference characteristics and charge guidance schemes. Full article

Developing electric vehicle (EV) energy storage technology is a strategic position from which the automotive industry can achieve low-carbon growth, thereby promoting the green transformation of the energy industry in China. This paper will reveal the opportunities, challenges, and strategies in relation to developing EV energy storage. First, this paper clarifies the strategic value and potential of developing EV energy storage under the carbon neutrality goal. Second, this paper demonstrates strategic opportunities and challenges during the development. Third, this paper proposes methods for creating a good market environment and business models. Finally, this paper suggests that relevant policies and regulations should be formulated and charts the course of technology development. The results show that EV energy storage technology has potential in terms of technology, the scale of development, and the user economy. The proposal of the carbon neutrality goal, the increasing market share of EVs, lower-cost and higher-efficiency batteries, etc., have all further accelerated the development of EV energy storage. The EV energy storage field should focus on developing battery technology, make advancements toward delivering longer cycle lives and improving the safety and availability of battery materials, and ramp up the R&D efforts with respect to developing vehicle-to-grid (V2G) management technologies. Simultaneously, it is necessary to create a business ecosystem centered on V2G operating platforms, constituting a process to which various players can contribute and achieve mutually beneficial results. It is also essential to formulate top-level strategic plans across industries and organizations, develop an electricity-trading mechanism as soon as possible, and promote the implementation of technical standards related to EV energy storage. Full article

In this paper, we propose a new approach to dynamic wireless charging that allows electric vehicles to charge wirelessly while in motion in both lanes on highways. The challenge is to locate the charging infrastructure on a highway between origin O and destination S (round trip) with heterogeneous battery vehicles, where each type of vehicle requires its allocation of charging segments on the road. We aim to ensure that each type of vehicle can complete a round trip without running out of battery charge while minimizing the number of charging segments and inverters on the road by studying both lanes simultaneously. We model the problem mathematically and validate it using a CPLEX optimizer for limited instances. Finally, we solve the problem using a hybrid approach that combines genetic algorithms and local search techniques to balance diversification and intensification. We have significantly improved the results found in the literature by reducing the number of inverters, which are expensive components in the charging infrastructure. Our approach takes advantage of utilizing a single inverter for both lanes of the highway, leading to cost savings and improved efficiency. Full article

In the case of electric vehicle drives, faults in the drive system or in the traction inverter, which controls the vehicle drive unit, could lead to abrupt and unpredictable motion as well as acceleration of the vehicle. In terms of functional safety, the typically existing, permanent mechanical connection of the drive machine with the drive wheels poses a high safety risk. In particular, unintended motion of the vehicle from a standstill is especially critical due to the high risk of injury to traffic participants. To reduce this risk, appropriate monitoring algorithms can be applied for the rapid detection of faulty operation. A corresponding algorithm for fault detection in the electric drive of a vehicle is presented in this paper. In addition to the description of the algorithms, various driving maneuvers of an electric single-wheel drivetrain are simulated in fault-free and faulty operation on a hardware-in-the-loop test bench. The focus here is on the consideration of driving-off operations. Full article

The growing use of DC/DC power converters has resulted in the requirement that their complex controllers be cheaper and smaller, thus using cost-effective implementations. For this purpose, it is necessary to decrease the computational burden in controller implementation to minimize the hardware requirements. This manuscript presents two methods for tuning an adaptive linear–quadratic–Gaussian voltage controller for a battery charger/discharger, implemented with a Sepic/Zeta converter, to work at any operating point. The first method is based on a lookup table to select, using the nearest method, both the state feedback vector and the observer gain vector, solving the Riccati’s differential equation offline for each practical operating point. The second method defines a polynomial function for each controller element that is based on the previous data corresponding to the system operating points. The adaptability of the two controllers to fixed voltage regulation and reference tracking was validated using simulations and experimental tests. The overshoot and settling time results were lower than 11% and 3.7 ms, which are in the same orders of magnitude of a control approach in which the equations are solved online. Likewise, three indices were evaluated: central processing unit capacity, cost, and performance. This evaluation confirms that the controller based on polynomial interpolation is the best option of the two examined methods due to the satisfactory balance between dynamic performance and cost. Despite the advantages of the controllers in being based on a lookup table and polynomial interpolation, the adaptive linear–quadratic–Gaussian has the benefit of not requiring an offline training campaign; however, the cost saving obtained with the lookup table controllers and polynomial interpolation controllers, due to the possible implementation on small-size microcontrollers with development tool simple and easy maintenance, will surely be desirable for a large number of deployed units, ensuring that those solutions are highly cost-effective. Full article

A three-phase interior permanent magnet (IPM) machine with 18-stator-slots/12-rotor-poles and concentrated armature winding is commercially employed as a 10 kW integrated-starter-generator in a commercial hybrid electric vehicle. For comprehensive and fair evaluation, a pair of flux-switching permanent magnet (FSPM) brushless machines, namely one stator permanent magnet flux-switching (SPM-FS) machine, and one rotor permanent magnet flux-switching (RPM-FS) machine, are designed and compared under the same DC-link voltage and armature current density. Firstly, a SPM-FS machine is designed and compared with an IPM machine under the same torque requirement, and the performance indicates that they exhibit similar torque density; however, the former suffers from magnetic saturation and low utilization of permanent magnets (PMs). Thus, to eliminate significant stator iron saturation and improve the ratio of torque per PM mass, an RPM-machine is designed with the same overall volume of the IPM machine, where the PMs are moved from stator to rotor and a multi-objective optimization algorithm is applied in the machine optimization. Then, the electromagnetic performance of the three machines, considering end-effect, is compared, including air-gap flux density, torque ripple, overload capacity and flux-weakening ability. The predicted results indicate that the RPM-FS machine exhibits the best performance as a promising candidate for hybrid electric vehicles. Experimental results of both the IPM and SPM-FS machines are provided for validation. Full article

This study determines the location of the minimum fast charging infrastructure for electric vehicles in the interurban route Riobamba–Quito in Ecuador using the methodology of the maximum distance between fast charges (MDFC). From the application of the method, a MDFC of 60 km and a basic highway charging infrastructure (BHCI) of six stations are obtained. The location is calculated by measuring the MDFC on the road using the desktop application Google Earth Pro. The proposal is validated by means of a mathematical model in Simulink, and two simulation scenarios are proposed. In the first one, the initial state of charge (SOC) is 95% and represents an EV with complete charging patterns, while in the second one, the initial SOC is 65% and represents incomplete charging patterns. The results indicate that for both simulation scenarios, the EV KIA SOUL 2016 can perform the specified round-trip routes using the proposed BHCI performing two fast charges of 20 min each way. In all cases, SOC values during operation remain above 20%. The results obtained allow us to establish that the proposed BHCI and its location are sufficient to allow the studied EV to complete the route. Full article

In road transportation, the market for electric vehicles (EVs) is considered a potential solution for addressing issues related to gas emissions and noise pollution. Due to the limited driving range of the EV battery pack, the charging process must be fast and safe for EV drivers. Wireless charging technology for EVs has gained attention in recent years, and in this research, the authors explore the analysis and design of a resonant magnetic wireless system for charging electric vehicles. The authors propose a design methodology for a serial–serial (SS) wireless system, which outlines how to determine the appropriate pad dimensions for transferring power to the EV battery. The design approach is crucial to attaining the best possible coupling performance and efficiency. Additionally, the magnetic design of the pad is validated using Ansys Maxwell software, and the proposed design is co-simulated using Ansys Simplorer to analyze the performance of the system. Simulation results demonstrate that the proposed model can transfer over 3.7 kW of power with an efficiency of over 90.02%. The paper also discusses the bifurcation phenomenon at the resonance condition to ensure maximum efficiency. Full article

As we face issues of fossil fuel depletion and environmental pollution, it is becoming increasingly important to transition towards clean renewable energies and electric vehicles (EVs). However, designing electric motors with high power density for EVs can be challenging due to space and weight constraints, as well as issues related to power loss and temperature rise. In order to overcome these challenges, a significant amount of research has been conducted on designing high-power-density electric motors with advanced materials, improved physical and mathematical modeling of materials and the motor system, and system-level multidisciplinary optimization of the entire drive system. These technologies aim to achieve high reliability and optimal performance at the system level. This paper provides an overview of the key technologies for designing high-power-density electric motors for EVs with high reliability and system-level optimal performance, with the focus on advanced magnetic materials and the proper modeling of core losses under two-dimensional or three-dimensional vectorial magnetizations. This paper will also discuss the major challenges associated with designing these motors and the possible future research directions in the field. Full article

The cumulative inverter losses and power consumption of a silicon insulated gate bipolar transistor (Si IGBT) and three types of silicon carbide metal-oxide-semiconductor field-effect transistors (SiC MOSFETs) were evaluated on an electric motor test bench under a worldwide harmonized light vehicles test cycle (WLTC). SiC MOSFETs showed higher performance than Si IGBT regardless of the motor type and test vehicles. In the case of driving an interior permanent magnet synchronous motor (IPMSM), the latest 4th generation SiC MOSFET (SiC-4G) in ROHM has the lowest inverter loss and energy consumption compared with the other generations. In the case of driving an induction motor (IM), on the other hand, the 2nd generation SiC MOSFET (SiC-2G) in ROHM has the best energy consumption despite the fact that the inverter losses of SiC-2G are slightly larger than the loss of SiC-4G. The latest or later generation power device does not necessarily contribute to better performance in a total system by simply replacing early power devices. Full article

Mass transport conversion to an electrified powertrain requires suitable strategies for processing electric vehicle (EV) batteries after their intended first service life. Due to aging mechanisms, EV batteries lose capacity over their period of use and become unsuitable for their initial application at some point. However, to expand their lifetime and to meet the sustainability demand for EVs, the usage of these batteries in so-called Re-X applications is under intense discussion. Until now, downstream processing has been subject to high uncertainty regarding the expected advances. While many issues on the technical and ecological side have been at least partially resolved, the economics are still under assessment. For this reason, this paper intends to give a well-based outlook on the costs and benefits of three chosen scenarios: reuse, repurpose, and recycle. It is expected that under the given national policies and global market conditions, growing quantities of retired EV batteries will return from the transportation markets. Consequently, the market potential for retired batteries in downstream applications will significantly increase, as well as calls for stable solutions. Full article

This paper presents an approach for the design and derivation for establishing a digital product twin for battery cells. A digital product twin is a virtual replica of a physical battery cell and can be used to predict and optimize quality properties and performance in real-time. The study focuses on pouch cell manufacturing and aims to map the large amount and variety of process information down to purchased parts and interim products. The approach for this study was to collect and analyze data from the physical production process and use this information to structure a digital battery product twin based on its product architecture. The main findings of this study indicate that a digital product twin can be effectively structured and implemented in a digital interface based on its product architecture in combination with data from the physical production process. The results of this study show the potential of digital product twins, in which statements about material, design, and behavior can be made using real information from production. Further research will focus on the practical application and implementation of digital product twins in a battery cell pilot production. Full article

Series-winding three-phase PMSMs have a higher bus voltage utilization than the conventional three-phase PMSMs with star connection. This topology is suitable for applications with a limited bus voltage. However, the zero-sequence current controller will reduce the bus voltage utilization of the series-winding PMSMs, which causes problems in the flux-weakening controller design. The conventional flux-weakening control algorithms will cause the series-winding PMSMs to enter the overmodulation region early and degrade the performance of the zero-sequence current suppression algorithm. In this paper, a new flux-weakening controller with a dynamic fundamental voltage limit (FW-DFVL) is designed for the series-winding three-phase PMSM traction system. Firstly, the space vector modulation method combines the proposed virtual zero-sequence vectors to realize both the fundamental current generation and the zero-sequence current suppression. The accurate bus voltage utilization in the fundamental current subspace can be derived from the proposed modulation method. Secondly, the gradient descent method generates the flux-weakening d-axis reference current with the dynamic fundamental voltage, which will converge faster than the conventional PI-based flux-weakening control scheme. Thirdly, the flux-weakening controller in the overmodulation region is also designed where the zero-sequence current will no longer be suppressed. The bus voltage utilization is V_dc in this operation mode. Finally, both the simulation and experimental results are utilized to verify the effectiveness of the proposed FW-DFVL, where faster dynamic performance and higher bus utilization are observed. Full article

The heavy reliance on petroleum-based fuels in the road transport industry, especially public transportation, results in substantial emissions of greenhouse gases. A significant obstacle on the path to a more sustainable public transportation sector is the employment of alternative fuels with lower environmental implications. Although there are several in-depth well-to-wheel studies for developed countries, extrapolating those results to gasoline markets in developing countries presents challenges because of significant differences in local fuel conditions and vehicle engine technologies. Notably, this study provides a national-level environmental life cycle assessment of alternative buses in Morocco and compares current diesel buses to potential hybrid diesel-electric buses, battery-electric buses, and fuel-cell buses from a well-to-wheel perspective. The model and approach used in this study applies to other countries with developing economies. Total energy consumption broken out by fuel type, greenhouse gas emissions, and criterion air pollutants is the primary outcome of this investigation. Findings highlight an energy cut of 44.7% from battery-electric buses, 36.3% from fuel-cell buses, and 31.7% from hybrid buses with regard to the current diesel buses. Additionally, alternative fuel buses proved to be less polluting in terms of greenhouse gas emissions with 50.8% less from battery-electric buses, 46.7% less from fuel-cell buses, and 26.8% less from hybrid buses; consequently, this would lead to reduced climate change, air pollution, acidification, and eutrophication, given the Egalitarian Environmental Impact Assessment. Ultimately, Morocco will have to tackle technological, financial, and institutional barriers to fully implement the change by 2030. Full article

A novel, multi-disciplinary approach is presented where experiments, system simulation and Computational Fluid Dynamics are combined for the electrical and thermal characterization of an air-cooled battery pack. As a case study, a Formula Student race car is considered and the procedure proposed consists of three steps: (1) experimental characterization of the battery cells under several thermal conditions; (2) thermal and electrical modeling of the battery stack with system simulation; (3) three-dimensional, time-dependent Conjugate Heat Transfer simulation of the whole battery pack to investigate the cooling performance of the chosen design, and to access fundamental quantities of the batteries, such as state of charge, temperature and ohmic heating. Future improvements of the current work are discussed, including the extension to a liquid-cooled design, battery aging consideration and model integration into a full vehicle system model. Full article

Lane-level route planning is a critical issue for a lane-level navigation system for autonomous vehicles. Current route-planning methods mainly focus on the road level and applying them directly to search for lane-level routes results in a reduction in search efficiency. In addition, previously developed lane-level methods lack consideration for vehicle characteristics and adaptability to multiple road network structures. To solve this issue, this study proposes an accelerated and refined lane-level route-planning algorithm based on a new lane-level road network model. First, five sub-layers are designed to refine the internal structure of the divided road and intersection areas so that the model can express multiple variations in road network structures. Then, a multi-level route-planning algorithm is designed for sequential planning at the road level, lane group level, lane section level, and lane level to reduce the search space and significantly improve routing efficiency. Last, an optimal lane determination algorithm considering traffic rules, vehicle characteristics, and optimization objectives is developed at the lane level to find the optimal lanes on roads with different configurations, including those with a constant or variable number of lanes while satisfying traffic rules and vehicle characteristics. Tests were performed on simulated road networks and a real road network. The results demonstrate the algorithm’s better adaptability to changing road network structures and vehicle characteristics compared with past hierarchical route planning, and its higher efficiency compared with direct route planning, past hierarchical route planning, and the Apollo route-planning method, which can better support autonomous vehicle navigation. Full article

The cell finishing process is the final stage in the production of a battery cell. Almost one third of the production costs of a battery cell are related to this part of the production. It includes a series of steps and technologies aimed at optimizing the battery cell’s performance, quality, and safety. The process is divided into three categories: pre-treatment, formation procedure, and quality testing. The order of the processes and the time required for each step can vary depending on the manufacturer and the cell format. Recent trends in optimizing the cell finishing process include the integration of a second filling process for larger prismatic cells and the optimization of the formation protocol or Electrochemical Impedance Spectroscopy (EIS) as possible methods for quality inspection. Efforts are also being made to reduce the pre-treatment time and improve the degassing process to ensure cell performance, quality, and safety. In this paper, all process steps of the cell finishing process are presented, and their function and technological implementation in the industry are explained. Future innovations are analyzed in terms of time to market and the potential to optimize the process in terms of quality, time, and cost. Full article

Lithium-ion batteries are seen as a key element in reducing global greenhouse gas emissions from the transport and energy sectors. However, efforts are still needed to minimize their environmental impact. This article presents a path towards a circular economy and more sustainable batteries, thanks to their reuse in mobile charging stations for electric vehicles. This work presents the results of characterization tests and modeling of second life batteries. The presented characterization test and electrical models can be used as references to evaluate the performance of aged batteries after their first life. Detailed test procedures and data results are provided in an open-access data paper. Full article

Public bus decarbonization is increasingly important to address the global issue of climate change. There are several challenges associated with large-scale introduction of zero-emission technologies in public fleets. This is especially the case in an extra-urban context, of mountain regions with challenging weather conditions. In this work the analysis of the state-of-the-art ZEBs, local bus lines, and timetables was performed to understand the best fit of technology—battery electric buses (BEBs) or fuel cell electric buses (FCEBs)—for each line in such a region. Further, a simulation tool was developed to calculate the compatibility of zero-emission technologies with the current needs of the public transportation considering distance, altitude difference, and climate conditions. The results show that a complete switch of the fleet is possible with a slight increase in the number of buses and that there is no clear difference in the distance covered in mountainous areas by BEBs versus FCEBs, but that both technologies can cover similar distances. The tool developed is not limited to bus fleets but can be applied to all kinds of fleets that cover clearly defined daily routes. Full article

Benefits from EV (Electric vehicles) and e-mobility include the reduction of local emissions of pollutants from particulate matter (PM_0.5, PM_5, and PM₁₀) and nitrogen oxides (NO_x and NO₂). Cities and urban agglomerations benefit the most from potential emission reductions from EVs due to the large number of cars utilized in most urban traffic systems. This abstract presents results from a corporate research and funding project in Baden-Wuerttemberg, Germany (LINOx BW) which facilitates the installation of 2358 charging points within 178 different sub-projects in 23 different cities, spanning a period of four years. Utilizing several different survey waves, data about outgoing currents from these publicly funded charging points are gathered. Converting this data utilizing car classifications and emission classes (HBEFA), the reduction of local nitrogen oxides is derived. Full article

In this paper, battery system architectures are methodologically derived in order to find the key type differences. In a first step, the system levels are identified and distinguished. In order to be able to completely cover the solution space of battery system architectures, a distinction is also made between mono- and multifunctional materials. Based on the system levels, a framework for possible architectures is derived. Four system architecture generations with a total of eight different types are identified and analyzed in the dimensions “Nomenclature”, “Approach”, “Omitted Components” and “Industry Examples”. In this way, upcoming system architectures, such as cell-to-pack and cell-to-chassis, can be clearly differentiated. Finally, fundamental product characteristics for the four system generations are derived and compared. Full article

Lithium-ion batteries (LIBs) have been proven to be increasingly popular and are the solution of choice for many companies and business models around the world. One major question for battery owners is how to deal with returning batteries if they still contain sufficient capacity for operation. In this case, those energy storages can still be used in different, less-required second-life applications, such as stationary battery storage systems, contributing to increased product sustainability and economic benefits at the same time. However, the second-life business model is still at an early stage of development due to the young EV market in combination with long vehicle lifetimes. As a consequence, there are several barriers in various thematic fields, complicating the rededication process for LIBs. This review paper focuses on a summary of barriers to second-life adoption published with scientific reference. Furthermore, barriers are clustered thematically to provide a transparent landscape picture and valuable insights into the rededication process of LIBs. Full article

A key factor in limiting global warming is the conversion of conventional electricity generation to renewable energy sources. However, a major obstacle is that renewable energy generation and energy demand often do not coincide in time, and energy must therefore be stored temporarily. Vehicle to grid (V2G) can be used to store excess renewable energy in battery electric vehicles (BEVs) and feed it back into the electric grid when needed. For effective V2G operation, the grid may have to be expanded, as the energy needs to be transported to BEVs. However, the grid should only be strengthened where renewable energy demand exceeds current grid capacity due to high grid expansion costs. This requires a method that determines the spatial distribution of V2G potential at a high resolution. Since such a method has not yet been reported in the existing literature, and so is developed in this paper. The method is demonstrated for the city of Berlin and its 448 sub-districts. For each sub-district, the method allows determining the percentage of residential and BEV energy demand that can be met by renewables if V2G is deployed, and answers the question of whether a full renewable supply is possible. The results show that BEVs can be effectively used as intermediate storage for renewable energy. If 30% of the BEVs participate in V2G, more than 99% of the energy demand of households and BEVs in Berlin can be covered by renewables on certain days. On the other hand, V2G deployment increases the average peak load in the districts by up to 100% and results in a nearly double load on vehicle batteries. High shares of renewable energy can be observed in districts with a high degree of motorization, which are predominantly found in the outskirts of the city. Full article

We developed and used methodology to analyze scientific publications in Scopus relating to vehicle electrification and associated key enabling technologies: batteries, fuel cells and electric machines with power electronics. The global research landscape was mapped, and an analysis of the 16 most active countries was carried out. Vehicle electrification publications are rewarded with a high citation impact, and they include corporate actors to a great extent. China dominates in vehicle electrification research as well as in the enabling technologies, and China’s position is set to become even more dominating. Battery research has grown rapidly with a high citation impact, whereas the volume of research for the other enabling technologies was more constant during 2017–2021. Automakers’ research that has led to scientific publications was specifically studied. Ford Motor Company was the automaker with the highest number of vehicle electrification publications during 2017–2021. A large share of the automakers’ publications was co-authored with academic actors, and such publications were rewarded with a higher citation impact than those without. However, the share of international co-publications among the automakers was meager. It is concluded that the analysis of vehicle electrification publications gives an overview of the rapidly developing field. Moreover, the analysis of automakers’ involvement in such research is one way of obtaining one perspective on their strategies and priorities. Full article

With the increasing adoption rate of electric vehicles, power peaks caused by many cars simultaneously charging on the same low-voltage grid can cause local overloading and power outages. Smart charging solutions should spread this load, but there is a residual risk of incidental peaks. A decentralized and autonomous technology called GridShield is being developed to reduce the likelihood of a transformer’s fuse blowing when other congestion solutions have failed. It serves as a measure of last resort to protect the grid against local power failures from unpredicted congestion by temporarily limiting the virtual capacity of charging stations. This paper describes the technical development and demonstrates how GridShield can keep a transformer load below a critical limit using simulations and real-world tests. It optimizes grid capacity while ensuring grid reliability. Full article

Electric vehicle battery second-life applications are gaining attention as a way to minimize the environmental impact and increase economic profits. However, the demand for stationary energy storage is expected to be saturated in the near future with these second-life batteries. This fact, in addition to the several technical and economic challenges of second-life batteries, promotes exploring other alternatives. This work analyses and compares these possible approaches in terms of battery degradation and economic profit. The results show that for large batteries, intensive Vehicle to Grid does not cause an early retirement of the battery and allows reducing the underuse of the battery. In addition, for the same battery size, Vehicle to Grid provides more economic profit than second-life applications. Nevertheless, only in a few cases does this appear to be more profitable than simply utilizing the battery for driving. Importantly, this study has shown how the assessment of the second-life tends to be too optimistic as a consequence of assuming a fixed End of Life threshold for the batteries. Full article

The economics of long haul trucking on both continuous and intermittent Electric Highways were evaluated from a technical perspective as alternatives to using conventional megawatt chargers. The study revealed complex and sensitive interplay between the various technical factors related to the vehicle, its battery pack and the configuration and construction of the electrified highway. Key preliminary outcomes showed that a 250 kW highway power supply level allows a 36 tonne truck to drive continuously without requiring off-road recharging, and it can operate with a battery pack of about 50% of the size required for a truck only using megawatt charging. For now, while there is no overwhelming case in favour of any particular technology, the study serves to highlight the relevant factors impacting anticipated design criteria for the electrification of highways. Full article

A shared autonomous electric vehicle (SAEV) fleet and the vehicle-to-grid (V2G) strategy both have great potential to reduce GHG emissions. As these concepts have complementary value, they are even more promising combined. However, to the best of our knowledge, no research has yet been conducted on locating charging infrastructure for SAEVs with V2G feasibility. For this construction, the challenge lies in the fact that both mobility demand (mainly for SAEVs) and energy (for any installation of charging infrastructure) have a major influence on this problem. To find the optimal charging infrastructure (CI) allocation for SAEVs with V2G operations, both mobility requirements and grid constraints must be considered. In this paper, we find that optimization models are the most frequently used method to solve the CI allocation problem. We conduct separate examinations of the V2G and SAEVs location optimization models that have been formulated in the literature, for which objective functions are used, and which constraints are considered (with respect to mobility and the electric grid). We find that SAEV and V2G models have overlapping elements, but remain disjunct in their respective perspectives. CI allocation for SAEVs mainly takes mobility into account, but tends to ignore grid constraints or impacts. On the other hand, CI allocation for V2G focuses on the distribution network and the grid, forgetting about mobility demand. To take advantage of the SAEV-V2G potential, future research should combine mobility and grid aspects to find the optimal CI locations for SAEVs with V2G feasibility. Full article

Signalized intersections can increase the vehicle stops and consequently increase the energy consumption by forcing stop-and-go dynamics on vehicles. Eco-driving with the help of connectivity is a solution that could avoid multiple stops and improve energy efficiency. In this paper, an eco-driving framework is developed, which finds the energy-efficient speed profile both up- and downstream of a signalized intersection in free-flow situations (eco-FF). The proposed framework utilizes the signal phasing and timing (SPaT) data that are communicated to the vehicle. The energy consumption model used in this framework is a combination of vehicle dynamics and time-dependent auxiliary consumption, which implicitly incorporates the travel time into the function and is validated with real-world test data. It is shown that, by using the proposed eco-FF framework, the vehicle’s energy consumption is notably reduced. Full article

Automated vehicles, predicted to be fully electric in future, are expected to reduce road fatalities and road traffic emissions. The lane departure warning system, an important feature of automated vehicles, utilize lane detection and tracking algorithms. Researchers are constrained to test their lane detection algorithms because of the small publicly available datasets. Additionally, those datasets may not represent differences in road geometries, lane marking and other details unique to a particular geographic location. Existing methods to develop the ground truth datasets are time intensive. To address this gap, this study proposed a framework for an interpolation approach for quickly generating reliable ground truth data. The proposed method leverages the advantage of the existing manual and time-slice approaches. A detailed framework for the interpolation approach is presented and the performance of the approach is compared with the existing methods. Video datasets for performance evaluation were collected in Melbourne, Australia. The results show that the proposed approach outperformed four existing approaches with a reduction in time for generating ground truth data in the range from 4.8% to 87.4%. A reliable and quick method for generating ground truth data, as proposed in this study, will be valuable to researchers as they can use it to test and evaluate their lane detection and tracking algorithms. Full article

Model predictive control (MPC) technology for multi-phase electric drives has received increasing attention in modern industries, especially in electric vehicles, marine electrical propulsion, and wind power generation. However, MPC has several challenges in controlling multi-phase electric drives, including the design of weighting factors, high computational complexity, large harmonic currents, heavy reliance on the system model, fault-tolerant control operation, common-mode voltage, and zero-sequence current hazards. Therefore, this paper gives a comprehensive review of the latest and most effective solutions to the existing major technical challenges and prospects for the future trends of MPC for multi-phase electric drives. Full article

Consumption habits are changing due to the development of new technologies around renewable energy, environmental awareness, and new incentive policies. Smart grids are seen as an effective way to accommodate more renewable energy, achieve better control of demand, and improve the operating conditions of the electrical system. However, electric vehicles, which are an environmentally friendly alternative, have very high market penetration and require efficient electrical management at charging stations. Among the factors that have a significant impact on electrical energy consumption are traffic conditions, which can seriously impact the efficiency of electric vehicles. Therefore, the focus is on developing charging infrastructure and reducing vehicle waiting time by optimally allocating electric vehicles to charging stations. To this end, an optimization approach is presented, based on the traffic conditions collected by the SUMO simulator. This approach enables each vehicle to be assigned to the appropriate station while maintaining its battery state of charge at a higher level. Full article

Increasing penetration of electric vehicles brings a set of challenges for the electricity system related to its energy, power and balance adequacy. Research related to this topic often requires estimates of charging demand in various forms to feed various models and simulations. This paper proposes a methodology to simulate charging demand for different driver types in a local energy system in the form of time series of charging sessions. The driver types are extracted from historical charging session data via data mining techniques and then characterized using a kernel density estimation process. The results show that the methodology is able to capture the stochastic nature of the drivers’ charging behavior in time, frequency and energy demand for different types of drivers, while respecting aggregated charging demand. This is essential when studying the energy balance of a local energy system and allows for calculating future demand scenarios by compiling driver population based on number of drivers per driver type. The methodology is then tested on a simulator to assess the benefits of smart charging. Full article

The race for road electrification has started, and convincing drivers to switch from fuel-powered vehicles to electric vehicles requires robust Electric Vehicle (EV) charging infrastructure. This article proposes an innovative EV charging demand estimation and segmentation method. First, we estimate the charging demand at a neighborhood granularity using aggregated cellular signaling data. Second, we propose a segmentation model to partition the total charging needs among different charging technology: normal, semi-rapid, and fast charging. The segmentation model, an approach based on the city’s points of interest, is a state-of-the-art method that derives useful trends applicable to city planning. A case study for the city of Brussels is proposed. Our demand estimation results heavily correlate with the government’s predictions under similar assumptions. The segmentation reveals clear city patterns, such as transportation hubs, commercial and industrial zones or residential districts, and stresses the importance of a deployment plan involving all available charging technologies. Full article

This research work deals with the problem of controlling a salient-pole permanent-magnet synchronous motor (SP-PMSM) used in hybrid electric vehicles. An adaptive nonlinear controller based on the backstepping technique is developed to meet the following requirements: control of the reference vehicle speed in the presence of load variation and changes in the internal motor parameters while keeping the reliability and stability of the vehicle. The complexity of the control problem lies on the system nonlinearity, instability and the problem of inaccessibility to measure all the internal parameters, such as inertia, friction and load variation. For this issue, an adaptive backstepping regulator is developed to estimate these parameters. On the basis of formal analysis and simulation, as well as test results, it is clearly shown that the designed controller achieves all the goals, namely robustness and reliability of the controller, stability of the system and speed control, considering the uncertainty parameters’ measurements. Full article

To enable the deployment of battery electric vehicles (BEVs) as passenger cars in the private transport sector, suitable charging infrastructure is crucial. In this paper, a methodology for the efficient spatial distribution of charging infrastructure is evaluated by investigating a scenario with a 100% market penetration of BEVs of (around 1.3 million vehicles) in Berlin, Germany. The goal of the evaluated methodology is the development of various charging infrastructure scenarios—including public and private charging—which are suitable to cover the entire charging demand. Therefore, these scenarios are investigated in detail with a focus on the number of public charging points, their spatial distributions, the available charging power, and the necessary capital costs. For the creation of these charging infrastructure scenarios, a placement model is developed. As input, it uses the data of a multi-agent transport simulation (MATSim) scenario of the metropolitan area of Berlin to evaluate and optimize different distributions of charging infrastructure. The model uses a genetic algorithm and the principle of multi-objective optimization. The capital costs of the charging points and the mean detour car drivers must undertake are used as the optimization criteria. Using these criteria, we expect to generate cost-efficient infrastructure solutions that provide high usability at the same time. The main advantage of the method selected is that multiple optimal solutions with different characteristics can be found, and suitable solutions can be selected by subsequently using other criteria. Besides the generated charging scenarios for Berlin, the main goal of this paper is to provide a valid methodology, which is able to use the output data of an agent-based, microscopic transport simulation of an arbitrary city or area (or even real driving data) and calculate different suitable charging infrastructure scenarios regarding the different optimization criteria. This paper shows a possible application of this method and provides suggestions to improve the significance of the results in future works. The optimized charging infrastructure solutions for the Berlin scenario show capital costs of between EUR 624 and 2950 million. Users must cover an additional mean detour of 254 m to 590 m per charging process to reach an available charging point. According to the results, a suitable ratio between the charging points and vehicles is between 11:1 and 5:1. A share of fast charging infrastructure (>50 kW) of less than ten percent seems to be sufficient if it is situated at the main traffic routes and highly frequented places. Full article

Smart charging of electric vehicles is a promising concept for solving the current challenges faced by connecting mobility and electricity within the context of the ongoing sustainable energy transition. It allows cost savings for the expansion and operation of the power grid and a more efficient use of renewable energies. However, wide implementation of smart charging requires further work on technical and regulatory issues and further development of standards, especially an end-to-end consistency of the control signals. A fully automated process, as well as customisable services and flexible tariffs, would also facilitate wider market penetration. The novelty of this paper is the consensus of German pilot projects funded within the German programme “Elektro-Mobil” on the communication channel between all stakeholders for the use cases of smart charging based on market price incentives. Within this consensus, the projects have illustrated how specific standards can facilitate the communication between smart charging stakeholders, become a reality in the pilot projects and should be applied to further use cases in the low-voltage network. This consensus results in a white paper. On this basis, the adjustment of the standards can be made to ensure the consistency of the control signals from the beginning of the control process up to the end. In an advanced Edition, solutions for the prioritisation and orchestration of the different control signals could be designed. Full article

Battery pack specific energy, which can be enhanced by minimising the mass of the battery thermal management system (BTMS), is a limit on electric fixed-wing flight applications. In this paper, the use of phase-change materials (PCMs) for BTMSs is numerically explored in the 3D domain, including an equivalent circuit battery model. A parametric study of PCM properties for effective thermal management is conducted for a typical one-hour flight. PCMs maintain an ideal operating temperature (288.15 K–308.15 K) throughout the entire battery pack. The PCM absorbs heat generated during takeoff, which is subsequently used to maintain cell temperature during the cruise phase of flight. In the control case (no BTMS), battery pack temperatures fall below the ideal operating range. We conduct a parametric study highlighting the insignificance of PCM thermal conductivity on BTMS performance, with negligible enhancement observed across the tested window (0.1–10 W m⁻¹ K⁻¹). However, the PCM’s latent heat of fusion is critical. Developers of PCMs for battery-powered flight must focus on enhanced latent heat of fusion, regardless of the adverse effect on thermal conductivity. In long-haul flight, an elongated cruise phase and higher altitude exasperate this problem. The unique characteristics of PCM offer a passive low-mass solution that merits further investigation for flight applications. Full article

As the bottom layer of the autonomous vehicle, path tracking control is a crucial element that provides accurate control command to the X-by-wire chassis and guarantees the vehicle safety. To overcome the deterioration of control performance for autonomous vehicle path-tracking controllers caused by modeling errors and parameter perturbation, an adaptive robust control framework is proposed in this paper. Firstly, the 2-DOF vehicle dynamic model is established and the non-singular fast terminal sliding mode control algorithm is adopted to formulate the control law. The unmeasured model disturbance and parameter perturbation is regarded as the system uncertainty. To enhance the control accuracy, the radial basis forward neural network is introduced to estimate such uncertainty in real time. Then, the dynamic model of an active front steering system is established. The model reference control algorithm is applied for the steering torque control considering model uncertainty brought by the dissipation of manufacturing and mechanical wear. Finally, the Simulink–CarSim co-simulation platform is used and the proposed control framework is validated in two test scenarios. The simulation results demonstrate the proposed adaptive robust control algorithm has satisfactory control performance and good robustness against the system uncertainty. Full article

If the energy transfer for charging the traction battery of an electric vehicle takes place wirelessly and with inductive components, the active area of the charging system must be monitored for safety reasons for the presence or intrusion of metallic objects that do not belong to the charging system. In the past, different concepts for such monitoring have been described. In this paper, passive inductive sensors are used and characterized based on practical measurements. With this type of sensor, the detectability of metallic foreign objects is very closely related to the characteristics of the magnetic field of the charging system. By optimizing the geometry of the sensor coils, the authors show how foreign object detection can be improved even in areas with low excitation of the foreign objects and the sensor coils by the magnetic field. For this purpose, a charging system, with which charging powers of up to 10 kW have been realized in the past, and standardized test objects are used. Furthermore, the thermal behavior of the metallic test objects was documented, which in some cases heated up to about 300 °C and above in a few minutes in the magnetic field of the charging system. The results show the capability of passive inductive sensors to detect metallic foreign objects. Based on the measurements shown here, the next step will be to simulate the charging system and the foreign object detection in order to establish the basis for a virtual development and validation of such systems. Full article

Plug-in electric vehicles (PEVs), consisting of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), combined with the decarbonization of the electricity sector, can significantly help reduce greenhouse gas emissions in the transport sector. This study used empirical data from 287 households with at least one plug-in electric vehicle in California between 2016 and 2020. We estimated electric vehicle miles traveled (eVMT), fuel consumption and utility factor at the household level, i.e., taking into consideration all vehicles. We also studied the effect of household-specific factors—such as frequency of overlaps between vehicles, frequency of charging and frequency of long-distance trips—on eVMT, utility factor and fuel consumption within two-car households. Our results indicate that PHEVs with a range of at least 35 miles have the potential to electrify a similar share of total household miles as some short range BEVs, or can reach up to 70% as much electrification as some long range BEVs and, thus, can play an important role in decarbonizing the transport sector. Full article

Electric vehicles rely on public fast charging when traveling outside a single charge range. Networks of fast charging hubs are a preferred solution, but should be deployed according to a design that avoids both redundant infrastructure representing overinvestment, and “charging deserts” which limit travel by EVs and thus inhibit EV adoption. We present a two-stage design strategy for a network of charging hubs relying on common public data including maps of roadways and electrical systems, and ubiquitous and readily accessible daily traffic volume data. First, the network design is based on the electrical distribution system, roadways, and a target inter-hub driving distance. Second, the number of fast chargers necessary at each hub to support expected vehicle kilometers is determined such that queuing to charge is infrequent. A case study to prepare Nova Scotia, Canada for the 2030 electric fleet of 15% of vehicles results in a network design with an average hub catchment area of 1230 km² and 354 electric vehicles per fast charger, and ensures that they are equitably distributed and can enable travel by EV throughout the jurisdiction. Full article

Electric road systems (ERS)—infrastructure that allows for charging while driving—are currently considered in Sweden for electrifying long-haul trucking. The technology can also charge battery electric passenger vehicles (BEVs). This study utilizes real-world car movement data in Sweden and detailed spatial analysis to explore to what extent ERS could displace stationary charging if it is available for BEVs and the expected benefits. We find that ERS utilization and the minimum battery ranges depend more on visited locations and home locations and less on the annual travel distances of car users. The median battery ranges required by rural residents are 15–18% greater than for urban residents. Our scenarios suggest that a mix of ERS and home-charging would achieve the most significant benefits. ERS with home charging reduces the required battery range by 62–71% in the main scenarios, and the net savings from smaller BEV batteries exceed the cost of ERS. Eliminating all stationary charging is feasible for many but not all vehicles. Utilizing ERS could also significantly reduce peak BEV charging by distributing charging throughout the day. We also find that there is a considerable difference between the maximum possible and minimum needed charging on ERS, which can significantly influence ERS revenues. Future studies can expand to include other modes (e.g., trucks) to provide more holistic assessments of economic benefits and charging needs. Full article

The Norwegian charging infrastructure ecosystem was investigated from a user perspective by (1) developing knowledge of end-user experiences with public charging, (2) mapping BEV owners and future owner’s user-friendliness needs and the extent to which these needs are met, (3) pointing at potential user-friendliness improvements, (4) mapping the charging infrastructure ecosystem and business models, and (5) developing scenarios for the future system development and the impact on charging infrastructure user-friendliness. The article draws on the literature, a BEV (battery electric vehicle) and ICEV (internal combustion engine vehicle) owner survey, 15 BEV owner interviews, 21 charging infrastructure actor interviews, and open information sources on the charger actors. The unregulated charging system evolved into a complex web of actors that developed their own charging networks following their individually sensible business models, which in sum led to serious user-friendliness issues. To gain access to all chargers, users need to interact with up to 20–30 apps and 13 payment systems, which comes on top of different plug types, power levels, and charger interfaces. Some actors support roaming, while others oppose it. OEMs want users to interface with chargers through the navigation system. In the future, the system will become even more complex and less user friendly as more actors join unless, e.g., consolidation, regulation, or independent network orchestrators reduce the complexity. Full article

The improvement of both the stability and economy of the four in-wheel motor drive (4IWMD) electric vehicle under complex drive cycles is currently a difficult problem in this field. A torque distribution method with the comprehensive goals of optimal torque distribution and energy efficiency, considering economy through energy efficiency for the 4IWMD electric vehicle, is proposed in this paper. Each component of the 4IWMD electric vehicle is modelled. The dynamic programming (DP) control algorithm is utilized for torque distribution between the front and rear in-wheel motors to obtain optimal torque distribution and energy efficiency in the 4IWMD electric vehicle. The simulation is performed on a co-simulation platform with the software of AVL Cruise and MATLAB/Simulink, considering a straight road. Compared to the fuzzy logic control algorithm, the simulation results are very promising, as the energy consumption of the electric vehicle was reduced by 22.68%, 20.73% and 21.84% under the WLTC, NEDC and customized IM240 driving cycle conditions, respectively, with the proposed DP control algorithm. The hardware-in-the loop (HIL) experimental results also indicate that the effectiveness of the proposed DP algorithm is verified under the NEDC, WLTC and IM240 driving cycles, when a straight road is considered. The proposed DP control algorithm not only reduces the vehicle energy consumption and guarantees the optimization of torque distribution, but also increases the driving range of the vehicle. Full article