2018-01-1342 Published 0 3 Apr 2018
© 2018 SAE International. All Rights Reserved.Research on Regenerative Braking Control Strategy
of Distributed EV based on Braking Intention
Hao Pan, Xuexun Guo, and Xiaofei Pei Wuhan University of Technology
Jin Pan and Jie Zhang Zhejiang Wanxiang Precision Industry Co.
Citation: Pan, H., Guo, X., Pei, X., Pan, J. et al., “Research on Regenerative Braking Control Strategy of Distributed EV based on Braking
Intention,” SAE Technical Paper 2018-01-1342, 2018, doi:10.4271/2018-01-1342.
Abstract
Focusing on distributed electric vehicles with in-wheel
motors, a novel regenerative braking control strategy based on braking intention is proposed. Firstly, a
design scheme for the regenerative braking system is described. Four in-wheel motors and an Electro-Hydraulic Braking (EHB) system are respectively designed for regenerative braking and hydraulic braking. Then, Braking intention recognition self-learning libraries are trained based on Hidden Markov Model method, which is validated by driver-in-loop tests. According to three speed states and four braking inten -
tions, the regenerative braking control strategy for multiple brake modes is developed. The coefficient of regenerative braking is defined to describe the intervening time and proportion of motor maximum regenerative braking. Eventually, the co-simulation results show that the proposed strategy can not only significantly improve the energy recovery capability, but also provide the coordinated control of regen -
erative braking and hydraulic braking, in consistence with the driver braking intention highly.
Introduction
With the environmental pollution and energy shortage more prominent, the pure electric vehicle (EV) becomes an important choice for the sustain -
able development of automotive industry. Distributed electric vehicle due to their high transmission efficiency and indepen -
dent wheel torque controlling, has obvious advantages in energy saving and active safety. Regenerative braking is the key technology of the distributed EV to improve the driving range [ 1]. Part of the original braking energy is converted into
the storage battery through motor regenerative braking, and then consumed in the automobile driving process appropri -
ately, realizing the energy recovery and reuse.
The research of regenerative braking system (RBS) has
been carried out in depth for automakers, TOYATA [ 2], Honda
[3] developed respective RBS for hybrid electric vehicle (HEV)
based on electronic servo technology. In order to improve system response speed of manual braking, ADVICS [ 4] devel -
oped a simple composition brake system based on conven -
tional ESC unit without the stroke simulator. The novel master cylinder with idle stroke realizes low-cost regenerative coop -
eration brake. With the advanced development of brake-by-wire technology, Electro-Hydraulic Braking (EHB) [ 5] plays
an important port in active braking due to its advantage over coordinated controlling. The ECB system of TOYOTA [ 6], the
SCB system of TWR [ 7], and the MK C1 system of Continental
are developed based on this design concept. Therefore, the EHB system is a better solution for hydraulic braking in RBS.
The electro-hydraulic brake torque distribution is the core
algorithm of regenerative braking. Gao designed three kinds of representative braking energy recovery strategy for single-drive HEV, and accomplished simulation studies through the city cycle tests [ 8]. Those strategies served as the important
reference for RBS control development. Kim proposed a genetic-based control logic to obtain the optimal brake torque distribution between the regenerative braking and vehicle stability enhancement [ 9]. Sun proposed an integrated control
strategy for an EV with double driving motor, including hybrid composite mode, parallel composite mode and pure hydraulic mode [ 10]. For distributed electric vehicles with four
in-wheel motors, its regenerative braking str
SAE_2018-01-1342_Research on Regenerative Braking Control Strategy of Distributed EV based on Braking Intention
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