Research on Energy Management Strategy for Range-Extended Electric Vehicles Based on Eco-Driving Speed

To achieve the optimal energy allocation between the auxiliary power unit (APU) and battery of connected automated range-extended electric vehicle (CAR-EEV), the hierarchical eco-driving control with dynamic game energy management were investigated and the optimization design of APU working mode was carried out from a multi-objective perspective. Initially, the acceleration and speed of the host vehicle were adjusted in real time, based on the driving status of the preceding vehicle, and the ecological driving speed was obtained in the adaptive car-following eco-driving mode. The dynamic game energy management strategy was proposed, leveraging the real-time interactive information between the vehicle and the traffic environment, and intelligently allocating and scheduling the energy flow within the powertrain. Dynamic game optimization was adopted to achieve dynamic decision-making and control optimization on whether to switch the APU operating speed or not. The multi-objective optimization analyses are carried out based on the weight coefficient matrix. The hierarchical dynamic game energy management strategy based on eco-driving speed (HDGEMS) is implemented through dynamic games and exhibits excellent performance. This strategy enables dynamic adjustment of power distribution between the APU and the battery, thereby allowing the APU to operate efficiently under optimal operating conditions. Meanwhile, it effectively reduces secondary charging losses and the dynamic switching time of the APU, and ultimately achieves energy optimization. Eventually, the results of simulation and experimental thoroughly indicated that economy improvement, emission reduction, and battery life enhancement of CAR-EEV were effectively kept in balance under the control of the proposed HDGEMS with intelligent optimization mode. New research ideas and technical directions are provided for the field of EMS, which is expected to promote technological progress in the industry.

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Publication Details

Journal
Applied Sciences
Published
2025-12-02
DOI
https://doi.org/10.3390/app152312738
Primary Topic
Electric and Hybrid Vehicle Technologies
Type
article
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article

Research on Energy Management Strategy for Range-Extended Electric Vehicles Based on Eco-Driving Speed

Kai‐Cheng Yang, Shunyao Li, Wencai Sun, Hanwu Liu et al.
Applied Sciences
Electric and Hybrid Vehicle Technologies
article

Research on Energy Management Strategy for Range-Extended Electric Vehicles Based on Eco-Driving Speed

Kai‐Cheng Yang, Shunyao Li, Wencai Sun, Hanwu Liu, Le Liu, Zihang Su, Q.Z. Xiao, Song Wang
article en

Abstract

To achieve the optimal energy allocation between the auxiliary power unit (APU) and battery of connected automated range-extended electric vehicle (CAR-EEV), the hierarchical eco-driving control with dynamic game energy management were investigated and the optimization design of APU working mode was carried out from a multi-objective perspective. Initially, the acceleration and speed of the host vehicle were adjusted in real time, based on the driving status of the preceding vehicle, and the ecological driving speed was obtained in the adaptive car-following eco-driving mode. The dynamic game energy management strategy was proposed, leveraging the real-time interactive information between the vehicle and the traffic environment, and intelligently allocating and scheduling the energy flow within the powertrain. Dynamic game optimization was adopted to achieve dynamic decision-making and control optimization on whether to switch the APU operating speed or not. The multi-objective optimization analyses are carried out based on the weight coefficient matrix. The hierarchical dynamic game energy management strategy based on eco-driving speed (HDGEMS) is implemented through dynamic games and exhibits excellent performance. This strategy enables dynamic adjustment of power distribution between the APU and the battery, thereby allowing the APU to operate efficiently under optimal operating conditions. Meanwhile, it effectively reduces secondary charging losses and the dynamic switching time of the APU, and ultimately achieves energy optimization. Eventually, the results of simulation and experimental thoroughly indicated that economy improvement, emission reduction, and battery life enhancement of CAR-EEV were effectively kept in balance under the control of the proposed HDGEMS with intelligent optimization mode. New research ideas and technical directions are provided for the field of EMS, which is expected to promote technological progress in the industry.

Applied SciencesVol. 15(23)
Jilin University (CN), Pakistan Army (PK), Jilin Agricultural University (CN), Changchun University (CN)
Openalex Percentile: Top 59%
Electric and Hybrid Vehicle Technologies
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