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Volume 13
Issue 12
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World Electr. Veh. J., Volume 13, Issue 12 (December 2022) – 22 articles

Cover Story (view full-size image): Grid-connected power electronics converters have been widely used in renewable energy conversion systems. Power devices’ fast switching can impose high-frequency common-mode voltages (HF-CMVs) onto the systems. Suitable space vector modulation (SVM) with reduced high-frequency common-mode voltages (HF-CMVs) for grid-connected current-source inverters (CSIs) has not been well investigated yet. In this study, the potential of active zero-state SVM (AZS-SVM) to suppress high-frequency common-mode voltages (HF-CMVs) is revealed and theoretically analyzed, which is different from existing approaches of modifying topology. A special five-segment sequence with an optimally selected third active space vector for AZS-SVM is proposed and applied for CSIs. View this paper
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16 pages, 10542 KiB  
Article
Design and Analysis of a Novel Adjustable SVAWT for Wind Energy Harvesting in New Energy Vehicle
by Zhen Zhao, Yongxin Li, Baifu Zhang, Changhong Wang, Zhangwei Yan and Qingcheng Wang
World Electr. Veh. J. 2022, 13(12), 242; https://doi.org/10.3390/wevj13120242 - 15 Dec 2022
Cited by 4 | Viewed by 2463
Abstract
The new energy vehicle is a robust measure to solve the problem of global warming. However, the new energy vehicle generally has the disadvantages of short mileage and difficulty in finding public chargers. The combination of wind energy harvest and new energy vehicle [...] Read more.
The new energy vehicle is a robust measure to solve the problem of global warming. However, the new energy vehicle generally has the disadvantages of short mileage and difficulty in finding public chargers. The combination of wind energy harvest and new energy vehicle can be conducive to the promotion of the new energy vehicle. This paper proposes a novel adjustable Savonius vertical axis wind turbine (SVAWT). It contains three parts: an energy absorption module, an energy recovery module, and an energy conversion module. The energy absorption module includes four blades with staggered distribution in two layers. The overlap ratio of the blades can be adjusted by the wind speed, which can ensure the SVAWT has a higher energy transfer efficiency. The energy recovery module adjusts the overlap ratio of the blades without interruption by utilizing the self-rotation and the orbital revolution of the gears. The energy conversion module converts mechanical energy into electric energy and supplies power for the vehicle after adjustment by the voltage regulator module. Based on actual operating data, it can be found that the variation trend of power of the blades absorbing is consistent with wind speed and increases with the wind speed. Under four actual operating conditions, the root mean square value of the blades absorbing power are 7.0 W, 7.1 W, 3.9 W, and 5.1 W, respectively. These results reveal that the proposed novel adjustable SVAWT has high recovery power potential and can provide a valuable solution to the practical applications of wind energy harvesting. Full article
(This article belongs to the Special Issue Trends and Emerging Technologies in Electric Vehicles)
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21 pages, 3063 KiB  
Article
Aspects of Foreign Object Detection in a Wireless Charging System for Electric Vehicles Using Passive Inductive Sensors
by Uwe Hentschel, Fiete Labitzke, Martin Helwig, Anja Winkler and Niels Modler
World Electr. Veh. J. 2022, 13(12), 241; https://doi.org/10.3390/wevj13120241 - 15 Dec 2022
Cited by 2 | Viewed by 2113
Abstract
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 [...] Read more.
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
(This article belongs to the Topic Coil, Circuit and Control Designs for Future Wireless Power Transfer Systems in Electric Vehicle Applications)
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13 pages, 4544 KiB  
Article
Virtual Constant Signal Injection-Based MTPA Control for IPMSM Considering Partial Derivative Term of Motor Inductance Parameters
by Qiang Miao, Qiang Li, Yamei Xu, Zhichen Lin, Wei Chen and Xinmin Li
World Electr. Veh. J. 2022, 13(12), 240; https://doi.org/10.3390/wevj13120240 - 14 Dec 2022
Cited by 3 | Viewed by 1500
Abstract
The dq-axis inductance parameter value of the Internal Permanent Magnet Synchronous Motor (IPMSM) will change with the dq-axis current. The Virtual Constant Signal Injection Method (VCSIM)-based Maximum Torque Per Ampere (MTPA) control ignores the partial derivative term of the dq-axis inductance to the [...] Read more.
The dq-axis inductance parameter value of the Internal Permanent Magnet Synchronous Motor (IPMSM) will change with the dq-axis current. The Virtual Constant Signal Injection Method (VCSIM)-based Maximum Torque Per Ampere (MTPA) control ignores the partial derivative term of the dq-axis inductance to the dq-axis current when extracting the partial derivative information of the torque to the dq-axis current. This will cause the current to deviate from the MTPA point, which will have a certain impact on the output capacity and efficiency of the motor torque. To solve the above problems, this paper proposes a simple and feasible compensation method by solving the partial derivative information between the dq-axis inductance and the dq-axis current. The experimental results show that the motor efficiency and torque output capability are significantly improved after applying the proposed strategy. Full article
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13 pages, 3231 KiB  
Article
Design of Obstacle Avoidance for Autonomous Vehicle Using Deep Q-Network and CARLA Simulator
by Wasinee Terapaptommakol, Danai Phaoharuhansa, Pramote Koowattanasuchat and Jartuwat Rajruangrabin
World Electr. Veh. J. 2022, 13(12), 239; https://doi.org/10.3390/wevj13120239 - 12 Dec 2022
Cited by 6 | Viewed by 3296
Abstract
In this paper, we propose a deep Q-network (DQN) method to develop an autonomous vehicle control system to achieve trajectory design and collision avoidance with regard to obstacles on the road in a virtual environment. The intention of this work is to simulate [...] Read more.
In this paper, we propose a deep Q-network (DQN) method to develop an autonomous vehicle control system to achieve trajectory design and collision avoidance with regard to obstacles on the road in a virtual environment. The intention of this work is to simulate a case scenario and train the DQN algorithm in a virtual environment before testing it in a real scenario in order to ensure safety while reducing costs. The CARLA simulator is used to emulate the motion of the autonomous vehicle in a virtual environment, including an obstacle vehicle parked on the road while the autonomous vehicle drives on the road. The target position, real-time position, velocity, and LiDAR point cloud information are taken as inputs, while action settings such as acceleration, braking, and steering are taken as outputs. The actions are sent to the torque control in the transmission system of the vehicle. A reward function is created using continuous equations designed, especially for this case, in order to imitate human driving behaviors. The results demonstrate that the proposed method can be used to navigate to the destination without collision with the obstacle, through the use of braking and dodging methods. Furthermore, according to the trend of DQN behavior, a better result can be obtained with an increased number of training episodes. This method is a non-global path planning method successfully implemented on a virtual environment platform, which is an advantage of this method over other autonomous vehicle designs, allowing for simulation testing and application with further experiments in future work. Full article
(This article belongs to the Special Issue Intelligent Vehicle Control Systems)
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16 pages, 5933 KiB  
Article
A Position Sensorless Control Strategy for BLDCM Driven by FSTPI Based on Flux-Linkage Function
by Xinmin Li, Guoqiang Jiao, Qiang Li, Wei Chen, Zhen Zhang and Guozheng Zhang
World Electr. Veh. J. 2022, 13(12), 238; https://doi.org/10.3390/wevj13120238 - 09 Dec 2022
Cited by 1 | Viewed by 1285
Abstract
This paper presents a new position sensorless control strategy for a brushless DC motor (BLDCM) driven by a four-switch three-phase inverter (FSTPI). This strategy introduces a flux-linkage function, which changes obviously at the time of the extremum jump. In the proposed strategy, the [...] Read more.
This paper presents a new position sensorless control strategy for a brushless DC motor (BLDCM) driven by a four-switch three-phase inverter (FSTPI). This strategy introduces a flux-linkage function, which changes obviously at the time of the extremum jump. In the proposed strategy, the extremum jump edge determines the six commutation points needed for motor commutation. Then the high-precision and reliable commutation of the BLDCM is realized. This strategy can be used on BLDCM driven by FSTPI. Compared with other position sensorless control methods for BLDCM driven by FSTPI, the proposed method does not need to set a threshold value to detect the commutation point. It can obtain six commutation points required for motor commutation without interpolation. This avoids commutation errors caused by threshold value setting and interpolation. In addition, this strategy adopts a three-phase current control method for BLDCM driven by FSTPI. It can effectively restrain the current distortion of the capacitor middle point connection phase. And the terminal voltage is calculated. It can avoid the error caused by hardware sampling and improve the accuracy of the position sensorless control strategy. The experimental results verify the correctness of the theory and the effectiveness of the method. Full article
(This article belongs to the Special Issue Electrical Machines Design and Control in Electric Vehicles)
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13 pages, 5809 KiB  
Article
Electric Vehicle Charging Data Analytics of Corporate Fleets
by Frederico Gonçalves, Liselene de Abreu Borges and Rodrigo Batista
World Electr. Veh. J. 2022, 13(12), 237; https://doi.org/10.3390/wevj13120237 - 07 Dec 2022
Cited by 1 | Viewed by 3465
Abstract
The advances in electric mobility, motivated by current sustainability issues, have led public and private organizations to invest in the electrification of their corporate fleets. To succeed in this transition, companies must mitigate the impacts of electrification on their fleet operation, in particular [...] Read more.
The advances in electric mobility, motivated by current sustainability issues, have led public and private organizations to invest in the electrification of their corporate fleets. To succeed in this transition, companies must mitigate the impacts of electrification on their fleet operation, in particular the ones on vehicle recharging. The increase in energy demand caused by electrification may require changes in the company electrical infrastructure, the installation of charging stations, and the proper planning of the recharging schedule, considering the particularities of each fleet and operation. In this context, data analytics is seen as an important tool to help companies to understand their charging fleet profile, supporting decision makers in making data-driven decisions regarding their charging infrastructure. This paper shows how data analytics could be applied to analyze the charging data of corporate electric fleets, adopting a business-oriented analysis method based on the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology. The analyses were performed on data collected from three different companies, with each one of them operating fleets of vehicles of different categories, i.e., ultra-light, light, and heavy vehicles. The results illustrate how data analytics, based on interactive reports and dashboards, can shed light on business questions related to the operation of electric vehicle corporate fleets. Full article
(This article belongs to the Special Issue Charging Infrastructure for EVs)
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15 pages, 5301 KiB  
Article
High-Frequency Common-Mode Voltage Reduced Space Vector Modulation for Grid-Connected Current-Source Inverter
by Hang Gao and Tahmin Mahmud
World Electr. Veh. J. 2022, 13(12), 236; https://doi.org/10.3390/wevj13120236 - 07 Dec 2022
Viewed by 1681
Abstract
Suitable space vector modulation (SVM) with reduced high-frequency common-mode voltages (HF-CMVs) for grid-connected current-source inverters (CSIs) have not been well investigated yet. In this study, the potential of active zero-state SVM (AZS-SVM) to suppress high frequency common-mode voltages (HF-CMVs) is revealed and theoretically [...] Read more.
Suitable space vector modulation (SVM) with reduced high-frequency common-mode voltages (HF-CMVs) for grid-connected current-source inverters (CSIs) have not been well investigated yet. In this study, the potential of active zero-state SVM (AZS-SVM) to suppress high frequency common-mode voltages (HF-CMVs) is revealed and theoretically analyzed, which is different from existing approaches of modifying topology. A special five-segment sequence with an optimally selected third active space vector for AZS-SVM is proposed and applied for CSIs. Simulation and experiments were completed on a (2.5 kW/208 V/6.94 A) grid-connected three-phase CSI. The results indicate that the proposed AZS-SVM mitigates HF-CMVs around unity and double control frequency by a factor of at least four times in contrast to that by conventional SVM, which validates the effectiveness of the proposed AZS-SVM to mitigate HF-CMVs generated by a grid-connected CSI. Full article
(This article belongs to the Special Issue Power Converters and Electric Motor Drives)
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23 pages, 4013 KiB  
Article
Research on Interval Optimal Scheduling Strategy of Virtual Power Plants with Electric Vehicles
by Taoyong Li, Jinjin An, Dongmei Zhang, Xiaohong Diao, Changliang Liu and Weiliang Liu
World Electr. Veh. J. 2022, 13(12), 235; https://doi.org/10.3390/wevj13120235 - 06 Dec 2022
Cited by 1 | Viewed by 1573
Abstract
The operation process of a virtual power plant is affected by many uncertainties, and how to ensure its comprehensive operation quality is a pressing challenge. For the virtual power plant incorporating electric vehicles, the interval number is used to describe the stochastic fluctuation [...] Read more.
The operation process of a virtual power plant is affected by many uncertainties, and how to ensure its comprehensive operation quality is a pressing challenge. For the virtual power plant incorporating electric vehicles, the interval number is used to describe the stochastic fluctuation of system uncertainties, and the optimization objectives are to (1) improve the operating economy, environmental protection, and grid load smoothing, (2) build a multi-objective interval optimal dispatching model considering the constraints of power balance and equipment operating characteristics, (3) solve the Pareto solution set by adopting the improved NSGA-II algorithm incorporating extreme scenario analysis, and (4) determine the optimal dispatching solution by the hierarchical analysis method. The median values of the determined optimal target intervals are 6456.11 yuan, 9860.01 kg, and 2402.56 kW. The algorithm shows that the proposed optimal dispatching strategy can effectively improve the economy of the virtual power plant and ensure that environmental protection and grid load smoothing requirements are met. Full article
(This article belongs to the Special Issue Novel Electric Vehicle Technology towards Low Carbon Future: Advanced Powertrain, Energy Management and Grid Interaction)
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15 pages, 5708 KiB  
Article
A Path Planning Method for Autonomous Vehicles Based on Risk Assessment
by Wei Yang, Cong Li and Yipeng Zhou
World Electr. Veh. J. 2022, 13(12), 234; https://doi.org/10.3390/wevj13120234 - 06 Dec 2022
Cited by 4 | Viewed by 2838
Abstract
In order to meet the requirements of vehicle automatic obstacle avoidance, a lane change trajectory planning method is proposed to meet the requirements of safety, comfort, and lane change efficiency. Firstly, the potential collision points that may exist are analyzed using information about [...] Read more.
In order to meet the requirements of vehicle automatic obstacle avoidance, a lane change trajectory planning method is proposed to meet the requirements of safety, comfort, and lane change efficiency. Firstly, the potential collision points that may exist are analyzed using information about surrounding vehicle movement and the road. Then, the safe lane change range for vehicles is obtained. Secondly, the control points of the fifth order Bézier curve are constrained to generate a series of path clusters in the optimal range. At the same time, the driver’s style and reaction time are taken into account in the risk assessment stage of the route using the improved artificial potential field method. Finally, the optimal path is selected by comprehensively considering lane-changing efficiency and comfort. In order to further verify the accuracy of the algorithm, real-vehicle experiments have been carried out on the autonomous vehicle platform. Under different driving styles, the vehicle can avoid obstacles perfectly while ensuring the smoothness of the path. Simulation and real-vehicle experiment results show that the proposed algorithm can provide an excellent solution for autonomous vehicles for lane changing and obstacle avoidance. Full article
(This article belongs to the Special Issue Theory, Method and Application of New Energy and Intelligent Transportation)
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15 pages, 4614 KiB  
Article
Obstacle-Avoidance Path-Planning Algorithm for Autonomous Vehicles Based on B-Spline Algorithm
by Pengwei Wang, Jinshan Yang, Yulong Zhang, Qinwei Wang, Binbin Sun and Dong Guo
World Electr. Veh. J. 2022, 13(12), 233; https://doi.org/10.3390/wevj13120233 - 05 Dec 2022
Cited by 5 | Viewed by 2298
Abstract
To solve the problem of the real-time path-planning of autonomous vehicles for obstacle avoidance on structured roads, a path-planning approach based on the B-spline algorithm is proposed in this paper. Firstly, the mechanism of driver path planning is analyzed, and a dynamic risk-identification [...] Read more.
To solve the problem of the real-time path-planning of autonomous vehicles for obstacle avoidance on structured roads, a path-planning approach based on the B-spline algorithm is proposed in this paper. Firstly, the mechanism of driver path planning is analyzed, and a dynamic risk-identification model based on the support vector machine is proposed. It combines the driver’s risk perception characteristics and a risk model. Then, the B-spline algorithm model is improved based on the risk-identification model. Furthermore, road features, road constraints and dynamic constraints are considered to further optimize the planning algorithm. To verify the path-planning approach proposed in this paper, a co-simulation experiment based on CarSim/Simulink is conducted. Results show that the improved algorithm is effective in static and dynamic obstacles avoidance. The algorithm can generate collision-free obstacle avoidance paths, and the paths meet the real-time requirements and dynamic constraints of obstacle avoidance scenarios. In addition, the proposed algorithm optimizes the path according to the driver’s operating characteristics, which can further improve the safety and comfort of autonomous vehicles. Full article
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16 pages, 1466 KiB  
Article
Optimizing Electric Motorcycle-Charging Station Locations for Easy Accessibility and Public Benefit: A Case Study in Surakarta
by Silvi Istiqomah, Wahyudi Sutopo, Muhammad Hisjam and Hendro Wicaksono
World Electr. Veh. J. 2022, 13(12), 232; https://doi.org/10.3390/wevj13120232 - 05 Dec 2022
Cited by 1 | Viewed by 2712
Abstract
Many benefits follow from the use of Electric Vehicles (EVs) to replace fossil fuel-based vehicles (FVs), i.e., improved transportation energy efficiency, reduced carbon and noise emissions, and the mitigation of tailpipe emissions. However, replacing conventional FVs with EVs requires the establishment of a [...] Read more.
Many benefits follow from the use of Electric Vehicles (EVs) to replace fossil fuel-based vehicles (FVs), i.e., improved transportation energy efficiency, reduced carbon and noise emissions, and the mitigation of tailpipe emissions. However, replacing conventional FVs with EVs requires the establishment of a suitable charging infrastructure representing a commonplace detail that blends into the landscape and is available in various locations. This research focuses on the infrastructure of Electric Motorcycles (EM), constituting a relatively dense network of charging stations (CS), which is an essential factor in accelerating the commercialization of EM in Indonesia. In this case study, we propose a Charging Infrastructure Optimization approach for placing charging stations to meet the demand posed by motorcycles. This study uses motorcycle user data as the initiation data for electric motorcycle users. The selection of charging station development points uses the calculation methods of the centrality index and scalogram, which describe the density of community activities. After the charging station’s construction point is obtained, the point is validated with the optimization model that has been designed with respect to the Maximal Covering Location Problem. We also analyze the benefits and costs of constructing this charging station to determine its feasibility. Full article
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19 pages, 1093 KiB  
Article
Toward Synthetic Data Generation to Enhance Skidding Detection in Winter Conditions
by Bryan McKenzie, Sousso Kelouwani and Marc-André Gaudreau
World Electr. Veh. J. 2022, 13(12), 231; https://doi.org/10.3390/wevj13120231 - 02 Dec 2022
Viewed by 1193
Abstract
In this paper, we propose the use of a neural network to identify lateral skidding events of road vehicles used during winter driving conditions. Firstly, data from a simulation model was used to identify the essential vehicle dynamics variables needed and to create [...] Read more.
In this paper, we propose the use of a neural network to identify lateral skidding events of road vehicles used during winter driving conditions. Firstly, data from a simulation model was used to identify the essential vehicle dynamics variables needed and to create the network structure. Then this network was retrained to classify real-world vehicle skidding events. The final network consists of a 3 layer network with 10, 5 and 1 output neurons 13 inputs, 4 outputs and a 5 step time delay. The retrained network was used on a limited set of real vehicle data and confirmed the effectiveness of the network classifying lateral skidding events. Full article
(This article belongs to the Special Issue Vehicle-Road Collaboration and Connected Automated Driving)
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16 pages, 3979 KiB  
Article
Wide Frequency PWM Rectifier Control System Based on Improved Deadbeat Direct Power Control
by Wei Chen, Shaozhen Li, Wenbo Sun, Kai Bi, Zhichen Lin and Guozheng Zhang
World Electr. Veh. J. 2022, 13(12), 230; https://doi.org/10.3390/wevj13120230 - 02 Dec 2022
Cited by 2 | Viewed by 1580
Abstract
The precision of deadbeat direct power control depends on the parameters of the system model. In wide frequency applications, such as multi- electric aircraft and electric vehicles, variations in frequency and resistive parameters will affect the control effect. The AC side voltage frequency [...] Read more.
The precision of deadbeat direct power control depends on the parameters of the system model. In wide frequency applications, such as multi- electric aircraft and electric vehicles, variations in frequency and resistive parameters will affect the control effect. The AC side voltage frequency of the generator rectifier varies widely, which will lead to a steady-state reactive power error in the deadbeat direct power control. In addition, the large temperature variation range during the operation of the multi-electric aircraft and electric vehicles leads to large changes in the filter inductance and line resistance of the AC side, and the model parameters do not match the actual parameters, which will further deteriorate the control accuracy. In this paper, a PWM rectifier control method is proposed for the occasions when the frequency and temperature change are in a wide range. Using repetitive control and power compensation, it solves the problems of steady-state reactive power error and control accuracy degradation caused by the mismatch of model parameters under severe operating conditions. The control method can precisely adjust the output DC voltage of PWM rectifier, and it also can maintain unity power factor and reduce the total harmonic distortion rate of the input current. The effectiveness of the proposed control method is verified by the experimental results. Full article
(This article belongs to the Special Issue Electrical Machines Design and Control in Electric Vehicles)
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16 pages, 4817 KiB  
Article
Performance Enhancement of Vehicle Mechatronic Inertial Suspension, Employing a Bridge Electrical Network
by Tianyi Zhang, Xiaofeng Yang, Yujie Shen, Xiaofu Liu and Tao He
World Electr. Veh. J. 2022, 13(12), 229; https://doi.org/10.3390/wevj13120229 - 01 Dec 2022
Cited by 2 | Viewed by 1623
Abstract
Inerters, a new type of mass element, have been successfully applied in various fields, such as in automotive and civil engineering. The development of a new element, named a mechatronic inerter, which consists of a ball-screw inerter and permanent magnet electric machinery, proves [...] Read more.
Inerters, a new type of mass element, have been successfully applied in various fields, such as in automotive and civil engineering. The development of a new element, named a mechatronic inerter, which consists of a ball-screw inerter and permanent magnet electric machinery, proves the feasibility of adopting electrical element impedances to simulate corresponding mechanical elements. In this paper, the structures of the bridge electrical network and series-parallel electrical network and their impedance characteristics are first introduced. Then, a seven-degree-of-freedom vehicle model is established. In addition, by comparison with passive suspension, a bridge network and a series-parallel network with various basic topologies are used to improve the vibration isolation performance of mechatronic inertial suspension, and the advantages of the bridge network (a) are demonstrated. Finally, a bridge electrical network (a) was designed and a real vehicle test was carried out. The test results showed that the mechatronic inertial suspension based on the bridge network (a) was superior to the passive suspension; the RMS (root-mean-square) values of the suspension working space and dynamic tire load of the left rear wheel suspension were reduced by 21.1% and 6.3%, respectively; and the RMS value of the centroid acceleration was improved by 1.8%. Full article
(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)
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10 pages, 4241 KiB  
Article
Top-Down Validation Framework for Efficient and Low Noise Electric-Driven Vehicles with Multi-Speed Gearbox
by Steffen Jäger, Jonas Schätzle and Tilmann Linde
World Electr. Veh. J. 2022, 13(12), 228; https://doi.org/10.3390/wevj13120228 - 30 Nov 2022
Viewed by 1664
Abstract
The shift towards e-mobility is resulting in new technological challenges. Thus, new, more efficient product development methods and a better product understanding are required. During product development, validation is essential both to achieve significantly increased knowledge of the system in question and to [...] Read more.
The shift towards e-mobility is resulting in new technological challenges. Thus, new, more efficient product development methods and a better product understanding are required. During product development, validation is essential both to achieve significantly increased knowledge of the system in question and to ensure that customers’ expectations of characteristics are met. Based on existing top-down validation approaches, this article discusses an innovative both-ends-against-the-middle-approach (BEATM) developed by the author. A validation framework which combines physical and virtual elements is presented. By way of example, a development approach for the toothing validation layer of an electric vehicle powertrain with a multi-speed gearbox is introduced. Full article
(This article belongs to the Special Issue EVS35—International Electric Vehicle Symposium and Exhibition (Oslo, Norway))
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23 pages, 3485 KiB  
Article
The Optimal Deployment of the Entry and Exit Gates of Electric Vehicles Wireless Charging Transmitters on Highways
by Mohammed Bourzik, Hassane Elbaz and Ahmed Elhilali Alaoui
World Electr. Veh. J. 2022, 13(12), 227; https://doi.org/10.3390/wevj13120227 - 28 Nov 2022
Cited by 2 | Viewed by 1243
Abstract
Dynamic wireless charging (DWC) facilitates the travel of electric vehicles (EVs) on highways because it can charge EVs without contact and it does not have a recharging time as it can charge vehicles in motion by a set of power transmitters on the [...] Read more.
Dynamic wireless charging (DWC) facilitates the travel of electric vehicles (EVs) on highways because it can charge EVs without contact and it does not have a recharging time as it can charge vehicles in motion by a set of power transmitters on the road. This work considers a highway road with DWC and a fleet of electric vehicles with heterogeneous batteries to begin a trip from the origin of the highway noted by O to the destination noted by S. As the usage of DWC is not free, this study seeks to install entry gates to the DWC if the vehicles need to charge their batteries and exit gates to the main road if the vehicles wish to stop the recharge. For this purpose, the first objective is to minimize the usage cost paid by each vehicle type to use the DWC during the trip on the highway. The second objective is to find the lower installation cost of the gates on the road. This work proposes to model the problem as a mathematical problem and validate it with the CPLEX optimizer using limited instances and, finally, solves the problem using the non-dominated sorting genetic algorithm (NSGA-II). Full article
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15 pages, 4439 KiB  
Article
Analysis of Active Suspension Control Based on Improved Fuzzy Neural Network PID
by Mei Li, Jiapeng Li, Guisheng Li and Jie Xu
World Electr. Veh. J. 2022, 13(12), 226; https://doi.org/10.3390/wevj13120226 - 24 Nov 2022
Cited by 9 | Viewed by 2138
Abstract
To improve the comfort and smoothness of vehicle driving and reduce the vehicle vibration caused by uneven road surface. In this paper, a new active suspension control strategy is pro-posed by combining a fuzzy neural network and a proportional-integral-derivative (PID) controller, taking body [...] Read more.
To improve the comfort and smoothness of vehicle driving and reduce the vehicle vibration caused by uneven road surface. In this paper, a new active suspension control strategy is pro-posed by combining a fuzzy neural network and a proportional-integral-derivative (PID) controller, taking body acceleration as the main optimization target and adjusting the parameters of the PID controller in real time. Meanwhile, a fuzzy neural network parameter optimization algorithm combining a particle swarm optimization algorithm and gradient descent method is proposed to realize offline optimization and online fine-tuning of fuzzy neural network parameters. Finally, the active suspension model of a 2-degree-of-freedom 1/4 vehicle is established using MATLAB/Simulink, and the proposed control scheme is verified through simulation studies. The results show that the active suspension system with a particle swarm-optimized fuzzy neural network control method improves the spring mass acceleration, dynamic deflection of suspension, and dynamic tire deformation by 30.4%, 17.8%, and 15.5%, respectively, compared with the passive suspension. In addition, there are also 14.6%, 12.1%, and 11.2% performance improvements, respectively, compared to the PID-controlled active suspension system. These results indicate that the control strategy proposed in this paper can improve the vehicle driving performance and can support the design and development of active suspension systems. Full article
(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)
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15 pages, 5683 KiB  
Article
A Strategy for Measuring Voltage, Current and Temperature of a Battery Using Linear Optocouplers
by Gopal Reddy Lakkireddy and Sudha Ellison Mathe
World Electr. Veh. J. 2022, 13(12), 225; https://doi.org/10.3390/wevj13120225 - 24 Nov 2022
Cited by 1 | Viewed by 4132
Abstract
Input voltage, current, and temperature measurement circuits are the vital concerns of a Battery Management System (BMS) in electric vehicles. There are several approaches proposed to analyze the parameters of voltage, current, and temperature of a battery. This paper proposes a BMS methodology [...] Read more.
Input voltage, current, and temperature measurement circuits are the vital concerns of a Battery Management System (BMS) in electric vehicles. There are several approaches proposed to analyze the parameters of voltage, current, and temperature of a battery. This paper proposes a BMS methodology that is designed using linear optocouplers. In this paper, the optocouplers are incorporated between the battery pack and the BMS, which can be used in automotive applications for accurate measurements. The functions of BMS, such as measuring the current, voltage, and temperature in real time, can be executed using the proposed methodology. Full article
(This article belongs to the Topic Battery Design and Management)
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10 pages, 2222 KiB  
Article
Optimizing Torque Delivery for an Energy-Limited Electric Race Car Using Model Predictive Control
by Thomas Maull and Adriano Schommer
World Electr. Veh. J. 2022, 13(12), 224; https://doi.org/10.3390/wevj13120224 - 24 Nov 2022
Viewed by 1863
Abstract
This paper presents a torque controller for the energy optimization of the powertrain of an electric Formula Student race car. Limited battery capacity within electric race car designs requires energy management solutions to minimize lap time while simultaneously controlling and managing the overall [...] Read more.
This paper presents a torque controller for the energy optimization of the powertrain of an electric Formula Student race car. Limited battery capacity within electric race car designs requires energy management solutions to minimize lap time while simultaneously controlling and managing the overall energy consumption to finish the race. The energy-managing torque control algorithm developed in this work optimizes the finite onboard energy from the battery pack to reduce lap time and energy consumption when energy deficits occur. The longitudinal dynamics of the vehicle were represented by a linearized first-principles model and validated against a parameterized electric Formula Student race car model in commercial lap time simulation software. A Simulink-based model predictive controller (MPC) architecture was created to balance energy use requirements with optimum lap time. This controller was tested against a hardware-limited and torque-limited system in a constant torque request and a varying torque request scenario. The controller decreased the elapsed time to complete a 150 m straight-line acceleration by 11.4% over the torque-limited solution and 13.5% in a 150 m Formula Student manoeuvre. Full article
(This article belongs to the Special Issue EVS35—International Electric Vehicle Symposium and Exhibition (Oslo, Norway))
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19 pages, 2279 KiB  
Article
On the Collaborative Use of EV Charging Infrastructures in the Context of Commercial Real Estate
by Joela Gauss, Sascha Gohlke and Zoltán Nochta
World Electr. Veh. J. 2022, 13(12), 223; https://doi.org/10.3390/wevj13120223 - 23 Nov 2022
Cited by 3 | Viewed by 2235
Abstract
Resource sharing in general is a means of solving the problem of infrequent and, thus, inefficient utilization of expensive or scarce resources. In this paper, we present an approach to run shared EV-charging infrastructures in the context of commercial real-estate facilities. Collaborating EV-charger [...] Read more.
Resource sharing in general is a means of solving the problem of infrequent and, thus, inefficient utilization of expensive or scarce resources. In this paper, we present an approach to run shared EV-charging infrastructures in the context of commercial real-estate facilities. Collaborating EV-charger owners thereby create a pool of chargers for shared use. In our work, we consider aspects of economic viability, desirability and technical feasibility as prerequisites of a successful solution. We formally prove that the basic economic potential of the proposed pooling with regard to overall infrastructure utilization is given. In order to operate the shared pool of charging points at a given location, the corresponding management software must fulfil specific requirements. Our prototype implementation that was realized as an extension of the open-source system Open E-Mobility demonstrates the technical feasibility of the sharing idea in a user-friendly way. Questionnaires and personal interviews conducted with owners of small and medium-sized businesses revealed that they would share charging stations if it helped overcome availability bottlenecks, thus improving customer and employee perception. Full article
(This article belongs to the Special Issue EVS35—International Electric Vehicle Symposium and Exhibition (Oslo, Norway))
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33 pages, 11924 KiB  
Article
Using an Intelligent Control Method for Electric Vehicle Charging in Microgrids
by Samaneh Rastgoo, Zahra Mahdavi, Morteza Azimi Nasab, Mohammad Zand and Sanjeevikumar Padmanaban
World Electr. Veh. J. 2022, 13(12), 222; https://doi.org/10.3390/wevj13120222 - 22 Nov 2022
Cited by 16 | Viewed by 3279
Abstract
Recently, electric vehicles (EVs) that use energy storage have attracted much attention due to their many advantages, such as environmental compatibility and lower operating costs compared to conventional vehicles (which use fossil fuels). In a microgrid, an EV that works through the energy [...] Read more.
Recently, electric vehicles (EVs) that use energy storage have attracted much attention due to their many advantages, such as environmental compatibility and lower operating costs compared to conventional vehicles (which use fossil fuels). In a microgrid, an EV that works through the energy stored in its battery can be used as a load or energy source; therefore, the optimal utilization of EV clusters in power systems has been intensively studied. This paper aims to present an application of an intelligent control method to a bidirectional DC fast charging station with a new control structure to solve the problems of voltage drops and rises. In this switching strategy, the power converter is modeled as a DC fast charging station, which controls the fast charging of vehicles with a new constant current or reduced constant current method and considers the microgrid voltage stability. The proposed method is not complicated because simple direct voltage control realizes the reactive power compensation, which can provide sufficient injected reactive power to the network. As a result, the test is presented on a fast charging system of electrical outlets with a proposed two-way reactive power compensation control strategy, in which AC/DC converters are used to exchange two-way reactive power to maintain the DC link voltage as well as the network bus voltage in the range of the basis. This charging strategy is carried out through the simulation of fast charge control, DC link voltage control, and reactive power compensation control to adjust the voltage and modify the power factor in the MATLAB software environment and is then verified. Finally, the results indicate that the proposed method can charge with high safety without increasing the battery’s maximum voltage. It can also significantly reduce the charging time compared to the common CV mode. Full article
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14 pages, 3946 KiB  
Article
MPC-Based Obstacle Avoidance Path Tracking Control for Distributed Drive Electric Vehicles
by Hongchao Wu, Huanhuan Zhang and Yixuan Feng
World Electr. Veh. J. 2022, 13(12), 221; https://doi.org/10.3390/wevj13120221 - 22 Nov 2022
Cited by 3 | Viewed by 1838
Abstract
A path tracking controller based on front wheel steering angle and additional yaw moment control is designed to achieve safe obstacle avoidance of distributed drive electric vehicles. Using sixth-degree polynomial at a given time with anti-collision and anti-rollover conditions, the path planning of [...] Read more.
A path tracking controller based on front wheel steering angle and additional yaw moment control is designed to achieve safe obstacle avoidance of distributed drive electric vehicles. Using sixth-degree polynomial at a given time with anti-collision and anti-rollover conditions, the path planning of obstacle avoidance is proposed. The front wheel steering angle and additional yaw moment are output by the Model Predictive Control (MPC) controller. The wheel torque is distributed by the torque distribution controller. Through additional yaw moment and the vertical force ratio of the wheel, the obstacle avoidance path tracking control is realized. The co-simulation platform is established with Carsim/Simulink. The obstacle avoidance path, model predictive controller and torque distribution controller designed in this paper are simulated. The results show that obstacle avoidance path and tracking controller for the distributed drive electric vehicles effectively meet the requirements of safe obstacle avoidance. Full article
(This article belongs to the Special Issue Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis)
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