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基于驾驶意图识别的增程电动汽车复合制动控制策略研究。

Research on Compound Braking Control Strategy of Extended-Range Electric Vehicle Based on Driving Intention Recognition.

机构信息

School of Automotive Engineering, Lanzhou Institute of Technology, Lanzhou 730050, China.

出版信息

Comput Intell Neurosci. 2022 Oct 7;2022:8382873. doi: 10.1155/2022/8382873. eCollection 2022.

Abstract

To improve the braking performance and braking energy feedback rate of extended-range electric vehicles, a driving intention recognition model is established based on Markov theory with brake pedal displacement, pedal displacement change rate, and pedal force as parameters, and the validity of the model is verified by actual vehicle test data. Based on the driving intention recognition model, a compound braking control strategy for extended-range electric vehicles is established with the constraints of braking force distribution and motor and battery characteristics. Cruise and MATLAB are used for joint simulation. The simulation results show that the compound braking system of extended-range electric vehicles with the compound braking control strategy based on brake intention recognition can work stably and effectively. On the premise of ensuring braking stability and safety, the braking energy recovery efficiency can be increased by 0.36% and the recovery rate can reach 12.88%. The compound braking system can effectively recover braking energy, improve the energy utilization rate of extended-range electric vehicles, and increase driving range.

摘要

为提高增程电动汽车的制动性能和制动能量回馈率,建立了以制动踏板位移、踏板位移变化率和踏板力为参数的基于马尔可夫理论的驾驶意图识别模型,并通过实车测试数据验证了模型的有效性。基于驾驶意图识别模型,建立了增程电动汽车的复合制动控制策略,该策略考虑了制动力分配和电机及电池特性的约束。采用 Cruise 和 MATLAB 进行联合仿真。仿真结果表明,基于制动意图识别的复合制动控制策略的增程电动汽车复合制动系统能够稳定有效地工作。在保证制动稳定性和安全性的前提下,可提高 0.36%的制动能量回收效率,回收效率可达 12.88%。复合制动系统能够有效回收制动能量,提高增程电动汽车的能量利用率,增加续驶里程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c98/9568300/fa2a867b1a90/CIN2022-8382873.001.jpg

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