A Logic Threshold Control Strategy to Improve the Regenerative Braking Energy Recovery of Electric Vehicles

Zongjun Yin, Xuegang Ma, Chunying Zhang (), Rong Su () and Qingqing Wang
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Zongjun Yin: School of Mechanical Engineering, Anhui Institute of Information Technology, Wuhu 241100, China
Xuegang Ma: School of Mechanical Engineering, Anhui Institute of Information Technology, Wuhu 241100, China
Chunying Zhang: School of Mechanical Engineering, Anhui Institute of Information Technology, Wuhu 241100, China
Rong Su: School of Mechanical Engineering, Anhui Institute of Information Technology, Wuhu 241100, China
Qingqing Wang: School of Mechanical Engineering, Anhui Institute of Information Technology, Wuhu 241100, China

Sustainability, 2023, vol. 15, issue 24, 1-33

Abstract: With increasing global attention to climate change and environmental sustainability, the sustainable development of the automotive industry has become an important issue. This study focuses on the regenerative braking issues in pure electric vehicles. Specifically, it intends to elucidate the influence of the braking force distribution of the front and rear axles on access to energy recovery efficiency. Combining the I curve of a pure electric vehicle and the boundary line of the Economic Commission of Europe (ECE) regulations, the braking force distribution relationship between the front and rear axles is formulated to satisfy braking stability. The maximum regenerative braking force of the motor is determined based on the motor torque characteristics and battery charging power, and the regenerative braking torque is optimized by combining the constraints of the braking strength, battery state of charge ( SOC ), and vehicle speed. Six road working conditions are built, including the New European Driving Cycle (NEDC), the World Light-Duty Vehicle Test Cycle (WLTC), Federal Test Procedure 72 (FTP-72), Federal Test Procedure 75 (FTP-75), the China Light-Duty Vehicle Test Cycle—Passenger (CLTC-P), and the New York City Cycle (NYCC). The efficiency of the regenerative braking strategy is validated by using the Simulink/MATLAB simulation. The simulation results show that the proposed dynamic logic threshold control strategy can significantly improve the energy recovery effect of electric vehicles, and the energy recovery efficiency can be improved by at least 25% compared to the situation without regenerative braking. Specifically, under the aforementioned road working conditions, the braking energy recovery efficiency levels are 27.69%, 42.18%, 49.54%, 47.60%, 49.28%, and 51.06%, respectively. Moreover, the energy recovery efficiency obtained by the current dynamic logic threshold is also compared with other published results. The regenerative braking control method proposed in this article makes the braking control of electric vehicles more precise, effectively reducing energy consumption and improving the driving range of electric vehicles.

Keywords: electric vehicles; regenerative braking; control strategy; logic threshold (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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