Energy efficiency optimization of electric vehicle driven by in-wheel motors

Gu, Jing; Ouyang, Minggao; Lu, Dongbin; Li, J.; Lu, Languang

doi:10.1007/s12239-013-0084-1

Cited by 64 publications

(40 citation statements)

References 9 publications

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“…The multi-objective programming is simplified as below, and it is suitable for off-line optimization: Equation (18) can easily be solved by off-line optimization. It is important to note here that in [16], the authors had done some research on the distribution of driving torque between the front axle and rear axle of a four-wheel-drive electric vehicle. In the development of the energy saving-oriented wheel torque distribution controllers, the functional relationship between energy efficiency and drive train output torque is needed.…”

Section: Off-line and On-line Optimizationmentioning

confidence: 99%

“…The accuracy of the distribution results must rely on that of the function established. In [16], a second-order function was deduced to describe the relationship between energy loss and drive train output torque based on theoretical analysis. Then the authors drew the conclusion that wheel torque equal division had better effect in vehicle energy saving than control allocation algorithms introduced in the literature.…”

Section: Off-line and On-line Optimizationmentioning

confidence: 99%

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Wheel Torque Distribution of Four-Wheel-Drive Electric Vehicles Based on Multi-Objective Optimization

Lin

2015

Energies

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Abstract:The wheel driving torque on four-wheel-drive electric vehicles (4WDEVs) can be modulated precisely and continuously, therefore maneuverability and energy-saving control can be carried out at the same time. In this paper, a wheel torque distribution strategy is developed based on multi-objective optimization to improve vehicle maneuverability and reduce energy consumption. In the high-layer of the presented method, sliding mode control is used to calculate the desired yaw moment due to the model inaccuracy and parameter error. In the low-layer, mathematical programming with the penalty function consisting of the yaw moment control offset, the drive system energy loss and the slip ratio constraint is used for wheel torque control allocation. The programming is solved with the combination of off-line and on-line optimization to reduce the calculation cost, and the optimization results are sent to motor controllers as torque commands. Co-simulation based on MATLAB ® and Carsim ® proves that the developed strategy can both improve the vehicle maneuverability and reduce energy consumption.

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Section: Off-line and On-line Optimizationmentioning

confidence: 99%

Section: Off-line and On-line Optimizationmentioning

confidence: 99%

Wheel Torque Distribution of Four-Wheel-Drive Electric Vehicles Based on Multi-Objective Optimization

Lin

2015

Energies

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“…Several recent studies presented driving strategies to improve efficiency of in-wheel electric vehicles. Gu et al [12] proposed a method for optimizing the efficiency of in-wheel electric vehicles through conversion between two-wheel drive and four-wheel drive while taking into consideration the loss of motor and inverter. However, there are many problems involving maximizing the motor efficiency by only relying on two-wheel/four-wheel conversion.…”

Section: Introductionmentioning

confidence: 99%

Torque Distribution Algorithm for an Independently Driven Electric Vehicle Using a Fuzzy Control Method

et al. 2015

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Abstract:The in-wheel electric vehicle is expected to be a popular next-generation vehicle because an in-wheel system can simplify the powertrain and improve driving performance. In addition, it also has an advantage in that it maximizes driving efficiency through independent torque control considering the motor efficiency. However, there is an instability problem if only the driving torque is controlled in consideration of only the motor efficiency. In this paper, integrated torque distribution strategies are proposed to overcome these problems. The control algorithm consists of various strategies for optimizing driving efficiency, satisfying driver demands, and considering tire slip and vehicle cornering. Fuzzy logic is used to determine the appropriate timing of intervention for each distribution strategy. A performance simulator for in-wheel electric vehicles was developed by using MATLAB/Simulink and CarSim to validate the control strategies. From simulation results under complex driving conditions, the proposed algorithm was verified to improve both the driving stability and fuel economy of the in-wheel vehicle.

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“…The recent evolution in the connected vehicle technology (CVT) which is a part of ITS can enhance these applications further by assessing and predicting real-time traffic conditions Ma et al, 2009). Furthermore, recent studies suggests that energy management and optimization of Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs) can contribute to a sustainable future and improve quality of life in developed countries as well as developing countries, if the source of electricity is renewable (Begley, 2011;Aggeri et al, 2008;Beaume and Midler, 2009;Wu et al, 2012;Gu et al, 2013). CVT can also enhance the operations of EVs by providing real-time connectivity between EVs, charging stations and electricity grid (Johnson et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Optimizing the performance of vehicle-to-grid (V2G) enabled battery electric vehicles through a smart charge scheduling model

Chowdhury

Bhavsar

et al. 2015

Int.J Automot. Technol.

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A smart charge scheduling model is presented for potential (1) vehicle-to-grid (V2G) enabled battery electric vehicle (BEV) owners who are willing to participate in the grid ancillary services, and (2) grid operators. Unlike most V2G implementations, which are considered from the perspective of power grid systems, this model includes a communication network architecture for connecting system components that supports both BEV owners and grid operators to efficiently monitor and manage the charging and ancillary service activities. This model maximizes the net profit to each BEV participant while simultaneously satisfying energy demands for his/her trips. The performance of BEVs using the scheduling model is validated by estimating optimal annual financial benefits under different scenarios. An analysis of popular BEV models revealed that one of the existing BEVs considered in the study can generate an annual regulation profit of $454, $394 and $318 when the average daily driving distance is 20 miles, 40 miles and 60 miles, respectively. All popular BEV models can completely compensate the energy cost and generate a positive net profit, through the application of the scheduling model presented in this paper, with an annual driving distance of approximately 15,000 miles. Simulation analysis indicated that the extra load distribution from the optimized BEV charging operations were well balanced compared to the unmanaged BEV operations.

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Energy efficiency optimization of electric vehicle driven by in-wheel motors

Cited by 64 publications

References 9 publications

Wheel Torque Distribution of Four-Wheel-Drive Electric Vehicles Based on Multi-Objective Optimization

Wheel Torque Distribution of Four-Wheel-Drive Electric Vehicles Based on Multi-Objective Optimization

Torque Distribution Algorithm for an Independently Driven Electric Vehicle Using a Fuzzy Control Method

Optimizing the performance of vehicle-to-grid (V2G) enabled battery electric vehicles through a smart charge scheduling model

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