Research

23 pages, 5445 KiB

Open AccessArticle

Modelling the Effect of Driving Events on Electrical Vehicle Energy Consumption Using Inertial Sensors in Smartphones

by David Jiménez, Sara Hernández, Jesús Fraile-Ardanuy, Javier Serrano, Rubén Fernández and Federico Álvarez

Energies 2018, 11(2), 412; https://doi.org/10.3390/en11020412 - 10 Feb 2018

Cited by 28 | Viewed by 6135

Abstract

Air pollution and climate change are some of the main problems that humankind is currently facing. The electrification of the transport sector will help to reduce these problems, but one of the major barriers for the massive adoption of electric vehicles is their [...] Read more.

Air pollution and climate change are some of the main problems that humankind is currently facing. The electrification of the transport sector will help to reduce these problems, but one of the major barriers for the massive adoption of electric vehicles is their limited range. The energy consumption in these vehicles is affected, among other variables, by the driving behavior, making range a value that must be personalized to each driver and each type of electric vehicle. In this paper we offer a way to estimate a personalized energy consumption model by the use of the vehicle dynamics and the driving events detected by the use of the smartphone inertial sensors, allowing an easy and non-intrusive manner to predict the correct range for each user. This paper proposes, for the classification of events, a deep neural network (Long-Short Time Memory) which has been trained with more than 22,000 car trips, and the application to improve the consumption model taking into account the driver behavior captured across different trips, allowing a personalized prediction. Results and validation in real cases show that errors in the predicted consumption values are halved when abrupt events are considered in the model. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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24 pages, 12641 KiB

Open AccessArticle

Development of a Cooperative Braking System for Front-Wheel Drive Electric Vehicles

by Di Zhao, Liang Chu, Nan Xu, Chengwei Sun and Yanwu Xu

Energies 2018, 11(2), 378; https://doi.org/10.3390/en11020378 - 06 Feb 2018

Cited by 27 | Viewed by 9308

Abstract

Most electric vehicles adopt cooperative braking systems that can blend friction braking torque with regenerative braking torque to achieve higher energy efficiency while maintaining a certain braking performance and driving safety. This paper presented a new cooperative regenerative braking system that contained a [...] Read more.

Most electric vehicles adopt cooperative braking systems that can blend friction braking torque with regenerative braking torque to achieve higher energy efficiency while maintaining a certain braking performance and driving safety. This paper presented a new cooperative regenerative braking system that contained a fully-decoupled hydraulic braking mechanism based on a modified electric stability control system. The pressure control algorithm and brake force distribution strategy were also discussed. Dynamic models of a front wheel drive electric car equipped with this system and a simulation platform with a driver model and driving cycles were established. Tests to evaluate the braking performance and energy regeneration were simulated and analyzed on this platform and the simulation results showed the feasibility and effectiveness of this system. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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11 pages, 4490 KiB

Open AccessArticle

Reducing Energy Demand Using Wheel-Individual Electric Drives to Substitute EPS-Systems

by Jürgen Römer, Philipp Kautzmann, Michael Frey and Frank Gauterin

Energies 2018, 11(1), 247; https://doi.org/10.3390/en11010247 - 20 Jan 2018

Cited by 11 | Viewed by 5591

Abstract

The energy demand of vehicles is influenced, not only by the drive systems, but also by a number of add-on systems. Electric vehicles must satisfy this energy demand completely from the battery. Hence, the use of power steering systems directly result in a [...] Read more.

The energy demand of vehicles is influenced, not only by the drive systems, but also by a number of add-on systems. Electric vehicles must satisfy this energy demand completely from the battery. Hence, the use of power steering systems directly result in a range reduction. The “e²-Lenk” joint project funded by the German Federal Ministry of Education and Research (BMBF) involves a novel steering concept for electric vehicles to integrate the function of steering assistance into the drive-train. Specific distribution of driving torque at the steered axle allows the steering wheel torque to be influenced to support the steering force. This provides a potential for complete substitution of conventional power steering systems and reduces the vehicle’s energy demand. This paper shows the potential of wheel-individual drives influencing the driver’s steering torque using a control technique based on classical EPS control plans. Compared to conventional power-assisted steering systems, a reduced energy demand becomes evident over a wide range of operating conditions. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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23 pages, 6209 KiB

Open AccessArticle

Coordinated Engine-Start Control of Single-Motor P2 Hybrid Electric Vehicles with Respect to Different Driving Situations

by Xiangyang Xu, Xiaoxiao Wu, Mick Jordan, Peng Dong and Yang Liu

Energies 2018, 11(1), 207; https://doi.org/10.3390/en11010207 - 15 Jan 2018

Cited by 11 | Viewed by 4605

Abstract

To cut down the costs caused by the additional starter, single-motor P2 hybrid electric vehicles (HEVs) make use of the driving motor to propel the vehicle as well as start the engine, and accordingly the engine-start control becomes more difficult. To satisfy the [...] Read more.

To cut down the costs caused by the additional starter, single-motor P2 hybrid electric vehicles (HEVs) make use of the driving motor to propel the vehicle as well as start the engine, and accordingly the engine-start control becomes more difficult. To satisfy the passengers’ demands, this paper developed different coordinated engine-start control strategies with respect to different situations. First, a detailed model for the single-motor P2 HEVs system was built and related parameters were presented. Then, the coordinated engine-start control architecture for the internal combustion engine (ICE), engine disconnect clutch (EDC), electric motor (EM) and 8-speed automatic transmission (AT) was analyzed. Considering with the different driving situations, soft start strategy and dynamical start strategy are individually proposed. Through the simulation, the above control strategies were validated in accordance with their control objectives. Last, to optimize the trade-off between driving performance and riding comfort, some key parameters were further discussed. This work not only decreases the difficulty of engine-start control in the single-motor P2 HEVs but also is helpful to improve the quality of engine-start. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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17 pages, 5763 KiB

Open AccessArticle

Impact on Congestion and Fuel Consumption of a Cooperative Adaptive Cruise Control System with Lane-Level Position Estimation

by Edgar Talavera, Alberto Díaz-Álvarez, Felipe Jiménez and José E. Naranjo

Energies 2018, 11(1), 194; https://doi.org/10.3390/en11010194 - 13 Jan 2018

Cited by 23 | Viewed by 4737

Abstract

In recent years, vehicular communications systems have evolved and allowed for the improvement of adaptive cruise control (ACC) systems to make them cooperative (cooperative adaptive cruise control, CACC). Conventional ACC systems use sensors on the ego-vehicle, such as radar or computer vision, to [...] Read more.

In recent years, vehicular communications systems have evolved and allowed for the improvement of adaptive cruise control (ACC) systems to make them cooperative (cooperative adaptive cruise control, CACC). Conventional ACC systems use sensors on the ego-vehicle, such as radar or computer vision, to generate their behavioral decisions. However, by having vehicle-to-X (V2X) onboard communications, the need to incorporate perception in the vehicle is drastically reduced. Thus, in this paper a CACC solution is proposed that only uses communications to make its decisions with the help of previous road mapping. At the same time, a method to develop these maps is presented, combining the information of a computer vision system to correct the positions obtained from the navigation system. In addition, the cut-in and cut-out maneuvers for a CACC platoon are taken into account, showing the tests of these situations in real environments with instrumented vehicles. To show the potential of the system in a larger-scale implementation, simulations of the behavior are provided under dense traffic conditions where the positive impact on the reduction of traffic congestion and fuel consumption is appreciated. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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6149 KiB

Open AccessArticle

Design and Analysis of a New Torque Vectoring System with a Ravigneaux Gearset for Vehicle Applications

by Yu-Fan Chen, I-Ming Chen, Joshua Chang and Tyng Liu

Energies 2017, 10(12), 2157; https://doi.org/10.3390/en10122157 - 17 Dec 2017

Cited by 11 | Viewed by 5910

Abstract

The purpose of this research is to develop a new torque vectoring differential (TVD) for vehicle applications and investigate its effect on vehicle dynamic control. TVD is a technology that is able to distribute the engine torque to the left and right driving [...] Read more.

The purpose of this research is to develop a new torque vectoring differential (TVD) for vehicle applications and investigate its effect on vehicle dynamic control. TVD is a technology that is able to distribute the engine torque to the left and right driving wheels at different ratios so that the yaw motion control can be realized. Attention has been paid to this technology in recent years because of its potential to improve the vehicle performance and driving safety. In this study, a new TVD design with a Ravigneaux gearset was developed. This new design is able to use only one pair of gearsets to generate two different speed ratios, and the weight and volume of the system can be reduced. To execute the research, current TVD designs were analyzed and their design principles were clarified. Next, a new TVD design with Ravigneaux gearset was proposed. Then the connecting manner and the gear ratio of the Ravigneaux gearset were discussed. The dynamic equation of the system was then derived and the operation of the system was simulated in a MATLAB program. Further simulation was performed with a vehicle dynamic model in SimulationX to demonstrate the effect of the new system. The results of this study show the potential of building a new TVD with a Ravigneaux gearset and can be helpful for further system development. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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4453 KiB

Open AccessArticle

Regenerative Intelligent Brake Control for Electric Motorcycles

by Juan Jesús Castillo Aguilar, Javier Pérez Fernández, Juan María Velasco García and Juan Antonio Cabrera Carrillo

Energies 2017, 10(10), 1648; https://doi.org/10.3390/en10101648 - 20 Oct 2017

Cited by 8 | Viewed by 6084

Abstract

Vehicle models whose propulsion system is based on electric motors are increasing in number within the automobile industry. They will soon become a reliable alternative to vehicles with conventional propulsion systems. The main advantages of this type of vehicles are the non-emission of [...] Read more.

Vehicle models whose propulsion system is based on electric motors are increasing in number within the automobile industry. They will soon become a reliable alternative to vehicles with conventional propulsion systems. The main advantages of this type of vehicles are the non-emission of polluting gases and noise and the effectiveness of electric motors compared to combustion engines. Some of the disadvantages that electric vehicle manufacturers still have to solve are their low autonomy due to inefficient energy storage systems, vehicle cost, which is still too high, and reducing the recharging time. Current regenerative systems in motorcycles are designed with a low fixed maximum regeneration rate in order not to cause the rear wheel to slip when braking with the regenerative brake no matter what the road condition is. These types of systems do not make use of all the available regeneration power, since more importance is placed on safety when braking. An optimized regenerative braking strategy for two-wheeled vehicles is described is this work. This system is designed to recover the maximum energy in braking processes while maintaining the vehicle’s stability. In order to develop the previously described regenerative control, tyre forces, vehicle speed and road adhesion are obtained by means of an estimation algorithm. A based-on-fuzzy-logic algorithm is programmed to carry out an optimized control with this information. This system recuperates maximum braking power without compromising the rear wheel slip and safety. Simulations show that the system optimizes energy regeneration on every surface compared to a constant regeneration strategy. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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2682 KiB

Open AccessArticle

Enumerative Optimization Procedure for the Gear Train Optimization Problem of a Two-Speed Dedicated Electric Transmission

by Xiangyang Xu, Zhifeng Chen, Yanjing Liu, Peng Dong and Yanfang Liu

Energies 2017, 10(9), 1362; https://doi.org/10.3390/en10091362 - 08 Sep 2017

Cited by 9 | Viewed by 3866

Abstract

Gear train optimization problems (GTOPs) can be very difficult. This paper proposes an enumerative optimization procedure (EOP) for the GTOP of a two-speed dedicated electric transmission (2DET) for electric vehicles (EVs). The EOP combines enumeration with the Min-Max Principle of Optimality (MMPO). First, [...] Read more.

Gear train optimization problems (GTOPs) can be very difficult. This paper proposes an enumerative optimization procedure (EOP) for the GTOP of a two-speed dedicated electric transmission (2DET) for electric vehicles (EVs). The EOP combines enumeration with the Min-Max Principle of Optimality (MMPO). First, the requirements of the EV and the requirements of manufacture and operation were checked in a dedicated order to obtain the feasible region of the GTOP. Then, the MMPO was implemented within the feasible region to reveal the global optimum in terms of the performance of the EV, the load capacity of the gears and the size of the gear train (GT). Results demonstrated that the EOP was effective in determining the feasible region and simultaneously and globally optimizing multiple criteria for the GTOP. The idea of combining enumeration with optimization, as the EOP presents, may be helpful to solve other GTOPs and provide global optima that are immediately practical and applicable. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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7852 KiB

Open AccessArticle

Particulate Matter and Gaseous Emission of Hydrous Ethanol Gasoline Blends Fuel in a Port Injection Gasoline Engine

by Maji Luo, Musaab O. El-Faroug, Fuwu Yan and Yinan Wang

Energies 2017, 10(9), 1263; https://doi.org/10.3390/en10091263 - 25 Aug 2017

Cited by 10 | Viewed by 5923

Abstract

The industrialization that increases day by day needs more and more power/fuel sources that are commonly available, abundant, renewable, and environmentally friendly. Recently, nearly all of the cities in China (PRC) have been influenced by haze. However, the pollutants from automobiles have always [...] Read more.

The industrialization that increases day by day needs more and more power/fuel sources that are commonly available, abundant, renewable, and environmentally friendly. Recently, nearly all of the cities in China (PRC) have been influenced by haze. However, the pollutants from automobiles have always been seriously considered to be the main contamination causes of the haze and that influence human health. This study concerns the impact of hydrous ethanol on in-cylinder pressure, particulate matter (PM), and gaseous emissions (oxides of nitrogen (NO_x) and unburned hydrocarbon (HC)) from a port fuel injection (PFI) gasoline engine. Tests were conducted on a four-cylinder port injection gasoline engine at different engine loads at an engine speed of 2000 rev/min for commercial gasoline, hydrous ethanol-gasoline blends (10% and 20% hydrous ethanol by volume), and an anhydrous ethanol-gasoline blend (20% anhydrous ethanol by volume). The results show that the peak in-cylinder pressure with the use of gasoline was the highest compared with the hydrous ethanol and anhydrous ethanol blends. Compared with the anhydrous ethanol blend, the hydrous ethanol blends performed well at a high load condition, equivalent to a low load. In addition, the total particulate number (PN) declines with an increase in engine operating loads for all of the fuels tested. The outcome of this study is an important reduction in PM number, mass emissions, and mean diameters of particles as the use of hydrous ethanol blends increases, while the form of the particulate size distribution remains the same. Furthermore, the NO_x emission is raised with a rise in engine load, and NO_x and HC emissions are reduced with the use of hydrous ethanol and anhydrous ethanol blend as equated with pure gasoline. Moreover, the correlation between the total particle number against NO_x and HC has been found; the number of particles increases when the NO_x emission decreases, and the opposite trend is exhibited for the HC emission. Therefore, it can be concluded that hydrous ethanol blends look to be a good selection for PM, NO_x, and HC reduction for gasoline engines. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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4979 KiB

Open AccessArticle

Investigation on a Power Coupling Steering System for Dual-Motor Drive Tracked Vehicles Based on Speed Control

by Li Zhai, Hong Huang and Steven Kavuma

Energies 2017, 10(8), 1118; https://doi.org/10.3390/en10081118 - 01 Aug 2017

Cited by 11 | Viewed by 5498

Abstract

Double-motor drive tracked vehicles (2MDTV) are widely used in the tracked vehicle industry due to the development of electric vehicle drive systems. The aim of this paper is to solve the problem of insufficient propulsion motor torque in low-speed, small-radius steering and insufficient [...] Read more.

Double-motor drive tracked vehicles (2MDTV) are widely used in the tracked vehicle industry due to the development of electric vehicle drive systems. The aim of this paper is to solve the problem of insufficient propulsion motor torque in low-speed, small-radius steering and insufficient power in high-speed large-radius steering. In order to do this a new type of steering system with a coupling device is designed and a closed-loop control strategy based on speed is adopted to improve the lateral stability of the vehicle. The work done entails modeling and simulating the 2MDTV and the proposed control strategy in RecurDyn and Matlab/Simulink. The simulation results show that the 2MDTV with the coupling device outputs more torque and power in both steering cases compared to the 2MDTV without the coupling device, and the steering stability of the vehicle is improved by using the strategy based on speed. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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6921 KiB

Open AccessArticle

A Control Strategy for Mode Transition with Gear Shifting in a Plug-In Hybrid Electric Vehicle

by Kyuhyun Sim, Sang-Min Oh, Ku-Young Kang and Sung-Ho Hwang

Energies 2017, 10(7), 1043; https://doi.org/10.3390/en10071043 - 20 Jul 2017

Cited by 10 | Viewed by 6828

Abstract

The mode transition from electric propulsion mode to hybrid propulsion mode is important with regard to the power management strategy of plug-in hybrid electric vehicles (PHEVs). This is because mode transitions can occur frequently depending on the power management strategies and driving cycles, [...] Read more.

The mode transition from electric propulsion mode to hybrid propulsion mode is important with regard to the power management strategy of plug-in hybrid electric vehicles (PHEVs). This is because mode transitions can occur frequently depending on the power management strategies and driving cycles, and because inadequate mode transitions worsen the fuel efficiency and drivability. A pre-transmission parallel PHEV uses a clutch between the internal combustion engine (ICE) and the electric motor (EM) to connect or disconnect the power source of the ICE for a mode transition. The mode transition requires additional energy consumption for clutch speed synchronization, and is accompanied by a drivetrain shock due to clutch engagement. This paper proposes a control strategy for the mode transition with gear-shifting to resolve the problems of energy consumption and drivetrain shock. Through the development of a PHEV performance simulator, we analyze the mode transition characteristics and propose a control strategy considering the vehicle acceleration and gear state. The control strategy reduces the duration required for the mode transition by moving the start time of the mode transition. This helps to improve energy efficiency while maintaining adequate drivability. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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5605 KiB

Open AccessArticle

Managing Traffic Flows for Cleaner Cities: The Role of Green Navigation Systems

by Fiamma Perez-Prada, Andres Monzon and Cristina Valdes

Energies 2017, 10(6), 791; https://doi.org/10.3390/en10060791 - 09 Jun 2017

Cited by 11 | Viewed by 5174

Abstract

Cities worldwide suffer from serious air pollution problems and are main contributors to climate change. Green Navigation systems have a great potential to reduce fuel consumption and exhaust emissions from traffic. This research evaluates the impacts of different percentages of green drivers on [...] Read more.

Cities worldwide suffer from serious air pollution problems and are main contributors to climate change. Green Navigation systems have a great potential to reduce fuel consumption and exhaust emissions from traffic. This research evaluates the impacts of different percentages of green drivers on traffic, CO₂, and NO_x over the entire Madrid Region. A macroscopic traffic model was combined with an enhanced macroscopic emissions model and a GIS (Geographic Information Systems) to simulate emissions on the basis of average vehicle speeds and traffic intensity at the link level. NO_x emissions are evaluated, taking into account not only the exhaust emissions produced by transport activity, but also the amount of the population exposed to these air pollutants. Results show up to 10.4% CO₂ and 13.8% NO_x reductions in congested traffic conditions for a 90% penetration of green drivers; however, the population’s exposure to NO_x increases up to 20.2%. Moreover, while traffic volumes decrease by 13.5% for the entire region, they increase by up to 16.4% downtown. Travel times also increase by 28.7%. Since green drivers tend to choose shorter routes through downtown areas, eco-routing systems are an effective tool for fighting climate change, but are ineffective to reduce air pollution in dense urban areas. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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1115 KiB

Open AccessArticle

The Optimal Road Grade Design for Minimizing Ground Vehicle Energy Consumption

by Junhui Liu, Lei Feng and Zhiwu Li

Energies 2017, 10(5), 700; https://doi.org/10.3390/en10050700 - 16 May 2017

Cited by 7 | Viewed by 4546

Abstract

Reducing energy consumption of ground vehicles is a paramount pursuit in academia and industry. Even though the road infrastructural has a significant influence on vehicular fuel consumption, the majority of the R&D efforts are dedicated to improving vehicles. Little investigation has been made [...] Read more.

Reducing energy consumption of ground vehicles is a paramount pursuit in academia and industry. Even though the road infrastructural has a significant influence on vehicular fuel consumption, the majority of the R&D efforts are dedicated to improving vehicles. Little investigation has been made in the optimal design of the road infrastructure to minimize the total fuel consumption of all vehicles running on it. This paper focuses on this overlooked design problem and the design parameters of the optimal road infrastructure is the profile of road grade angle between two fixed points. We assume that all vehicles on the road follow a given acceleration profile between the two given points. The mean value of the energy consumptions of all vehicles running on the road is defined as the objective function. The optimization problem is solved both analytically by Pontryagin’s minimum principle and numerically by dynamic programming. The two solutions agree well. A large number of Monte Carlo simulations show that the vehicles driving on the road with the optimal road grade consume up to 31.7% less energy than on a flat road. Finally, a rough cost analysis justifies the economic advantage of building the optimal road profile. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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1783 KiB

Open AccessArticle

Electric Vehicle Market Penetration and Impacts on Energy Consumption and CO₂ Emission in the Future: Beijing Case

by Qian Zhang, Xunmin Ou, Xiaoyu Yan and Xiliang Zhang

Energies 2017, 10(2), 228; https://doi.org/10.3390/en10020228 - 15 Feb 2017

Cited by 48 | Viewed by 8825

Abstract

This study focuses on the development of electric vehicles (EV) in the private passenger vehicle fleet in Beijing (China), analyzes how EVs will penetrate in the market, and estimates the resulting impacts on energy consumption and CO₂ emissions up to 2030. A [...] Read more.

This study focuses on the development of electric vehicles (EV) in the private passenger vehicle fleet in Beijing (China), analyzes how EVs will penetrate in the market, and estimates the resulting impacts on energy consumption and CO₂ emissions up to 2030. A discrete choice model is adopted with consideration of variables including vehicle technical characteristics, fuel prices, charging conditions and support policies. Results show that by 2030, without technological breakthrough and support policies, the market share of EV will be less than 7%, with gasoline dominating the energy structure. With fast technological progress, charging facility establishment, subsidies and tax breaks, EVs will account for 70% of annual new vehicle sales and nearly half of the vehicle stock by 2030, resulting in the substitution of nearly 1 million tons of gasoline with 3.2 billion kWh electricity in 2030 and the reduction of 0.6 million tons of CO₂ emission in 2030. Technological progress, charging conditions and fuel prices are the top three drivers. Subsidies play an important role in the early stage, while tax and supply-side policies can be good options as long-term incentives. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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5231 KiB

Open AccessArticle

Robust Clamping Force Control of an Electro-Mechanical Brake System for Application to Commercial City Buses

by Sangjune Eum, Jihun Choi, Sang-Shin Park, Changhee Yoo and Kanghyun Nam

Energies 2017, 10(2), 220; https://doi.org/10.3390/en10020220 - 14 Feb 2017

Cited by 15 | Viewed by 7169

Abstract

This paper proposes a sensor-less robust force control method for improving the control performance of an electro-mechanical brake (EMB) which is applicable to commercial city buses. The EMB generates the accurate clamping force commanded by a driver through an independent motor control at [...] Read more.

This paper proposes a sensor-less robust force control method for improving the control performance of an electro-mechanical brake (EMB) which is applicable to commercial city buses. The EMB generates the accurate clamping force commanded by a driver through an independent motor control at each wheel instead of using existing mechanical components. In general, an EMB undergoes parameter variation and a backdrivability problem. For this reason, the cascade control strategy (e.g., force-position cascade control structure) is proposed and the disturbance observer is employed to enhance control robustness against model variations. Additionally, this paper proposed the clamping force estimation method for a sensor-less control, i.e., the clamping force observer (CFO). Finally, in order to confirm the performance and effectiveness of a proposed robust control method, several experiments are performed and analyzed. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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4290 KiB

Open AccessArticle

A Mixed Logical Dynamical-Model Predictive Control (MLD-MPC) Energy Management Control Strategy for Plug-in Hybrid Electric Vehicles (PHEVs)

by Jing Lian, Shuang Liu, Linhui Li, Xuanzuo Liu, Yafu Zhou, Fan Yang and Lushan Yuan

Energies 2017, 10(1), 74; https://doi.org/10.3390/en10010074 - 10 Jan 2017

Cited by 32 | Viewed by 6080

Abstract

Plug-in hybrid electric vehicles (PHEVs) can be considered as a hybrid system (HS) which includes the continuous state variable, discrete event, and operation constraint. Thus, a model predictive control (MPC) strategy for PHEVs based on the mixed logical dynamical (MLD) model and short-term [...] Read more.

Plug-in hybrid electric vehicles (PHEVs) can be considered as a hybrid system (HS) which includes the continuous state variable, discrete event, and operation constraint. Thus, a model predictive control (MPC) strategy for PHEVs based on the mixed logical dynamical (MLD) model and short-term vehicle speed prediction is proposed in this paper. Firstly, the mathematical model of the controlled PHEV is set-up to evaluate the energy consumption using the linearized models of core power components. Then, based on the recognition of driving intention and the past vehicle speed data, a nonlinear auto-regressive (NAR) neural network structure is designed to predict the vehicle speed for known driving profiles of city buses and the predicted vehicle speed is used to calculate the total required torque. Next, a MLD model is established with appropriate constraints for six possible driving modes. By solving the objective function with the Mixed Integer Linear Programming (MILP) algorithm, the optimal motor torque and the corresponding driving mode sequence within the speed prediction horizon can be obtained. Finally, the proposed energy control strategy shows substantial improvement in fuel economy in the simulation results. Full article

(This article belongs to the Special Issue Methods to Improve Energy Use in Road Vehicles)

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