Optimal Control of a Hybrid Electric Vehicle Based on Fuzzy-PID Torque Identification

Abstract

Abstract:

A method wss put forward based on fuzzy-PID torque identification K, thus the drive mode of the vehicle was preliminarily decided by K. The particle swarm-ant colony algorithm was used to optimize the key parameters of the control strategy and the power components of the vehicle. After optimization, fuel consumption and emissions were reduced with power performances guaranteed. The optimized control strategy was simulated hardware in loop. The results indicate that the control strategy based on fuzzy-PID torque identification can realize basic energy management, and the control effectiveness is better than the controller without fuzzy-PID torque identification.

Key words: plug-in hybrid electric vehicle, fuzzy-PID, particle swarm-ant colony algorithm, hardware in loop(HIL) simulation

摘要：

提出了一种基于模糊PID扭矩识别系数K的计算方法，并利用K对驱动模式进行初步判断。使用粒子群-蚁群组合优化算法对控制策略中的关键控制参数及部分动力系统参数进行了优化。优化后，在保证整车动力性的基础上，油耗和排放都有所降低。对优化后的控制策略进行了硬件在环仿真，仿真结果表明，基于模糊PID扭矩识别的控制策略可以实现基本的能量管理，且控制效果优于未引入模糊PID扭矩识别的控制策略。

关键词: 插电式混合动力汽车, 模糊PID, 粒子群-蚁群算法, 硬件在环仿真

CLC Number:

U469.72

Qian Lijun, Qiu Lihong, Chen Peng. Optimal Control of a Hybrid Electric Vehicle Based on Fuzzy-PID Torque Identification[J]. China Mechanical Engineering, 2015, 26(13): 1752-1759.

钱立军, 邱利宏, 陈朋. 基于模糊PID扭矩识别的混合动力汽车优化控制[J]. 中国机械工程, 2015, 26(13): 1752-1759.

References

[1]崔纳新，步刚，吴剑，等. Plug-In并联式混合动力汽车实时优化能量管理策略[J].电工技术学报，2011，26(11)：155-160.
Cui Naxin，Bu Gang，Wu Jian，et al. Real-time Optimization of Energy Management Strategy for Plug-in Parallel Hybrid Electric Vehicles[J]. Transactions of China Electrotechnical Society，2011，26(11)：155-160.
[2]钱立军，邱利宏，辛付龙，等. 插电式四驱混合动力汽车能量管理与转矩协调控制策略[J]. 农业工程学报，2014，30(19)：55-64.
Qian Lijun，Qiu Lihong，Xin Fulong，et al. Energy Management and Torque Coordination Control for Plug-in 4WD Hybrid Electric Vehicle[J]. Transactions of the Chinese Society of Agricultural Engineering，2014，30(19)： 55-64.
[3]王润才，何仁，愈剑波，等. 基于遗传算法的插电式串联混合动力汽车动力参数优化[J].中国机械工程，2013，24(18)：2544-2549.
Wang Runcai，He Ren，YuJianbo，et al. Parameter Optimization of a PSHEV Based on Genetic Algorithm[J]. China Mechanical Engineering，2013，24(18)：2544-2549.
[4]尹安东，赵韩，张辉. 基于遗传-蚁群算法的PHEB模糊控制策略优化[J].中国机械工程，2011，22(14)：1754-1759.
Yin Andong，Zhao Han，Zhang Hui. Optimization of Fuzzy Control Strategy for Parallel Hybrid Electric Bus Based on Genetic-ant Colony Algorithm[J]. China Mechanical Engineering，2011，22(14)：1754-1759.
[5]陈可亮. 并联混合动力电动汽车能量管理系统智能控制策略研究[D]. 长沙：湖南大学，2011.
[6]王庆年，唐先智，王鹏宇，等. 基于神经网络的混合动力汽车驾驶意图识别方法[J].农业机械学报，2012，43(8)：32-36.
Wang Qingnian，Tang Xianzhi，Wang Pengyu，et al. Driving Intention Identification Method for Hybrid Vehicles Based on Neural Network[J]. Transactions of the Chinese Society for Agricultural Machinery，2012，43(8)：32-36.
[7]Wang Jun，Wang Qiangnian，Wang Pengyu，et al. Adaptive Shift Control Strategy Based on Driving Style Recognition[J]. SAE Technical Paper，2013-01-2486.
[8]王庆年，唐先智，王鹏宇，等. 基于驾驶意图识别的混合动力汽车控制策略[J].吉林大学学报(工学版)，2012，42(4)：789-795.
Wang Qingnian，Tang Xianzhi，Wang Pengyu，et al. Control Strategy of Hybrid Electric Vehicle Based on Driving Intention Ddentification[J]. Journal of Jilin University(Engineering and Technology Edition)，2012，42(4)：789-795.
[9]杨观赐，李少波，璩晶磊，等. 基于Pareto最优原理的混合动力汽车多目标优化[J]. 上海交通大学学报，2012，46(8)：1297-1304.
Yang Guanci，Li Shaobo，Qu Jinglei，et al. Multi-objective Optimization of Hybrid Electrical Vehicle Based on Pareto Optimality[J]. Journal of Shanghai Jiaotong University，2012，46(8)：1297-1304.
[10]Lin C C, Peng H, Grizzle J W, et al. Power Management Strategy for Parallel Hybrid Electric Truck[J]. IEEE Transactions on Control System Technology, 2003, 11(6):839-849.
[11]秦大同，彭志远，刘永刚，等. 基于工况识别的混合动力汽车动态能量管理策略[J]. 中国机械工程，2014，25(11)：1550-1555.
Qin Datong，Peng Zhiyuan，Liu Yonggang，et al. Dynamic Energy Management Strategy of HEV Based on Driving Pattern Recognition[J]. China Mechanical Engineering，2014，25(11)：1550-1555.
[12]王欣，李高，朱万力，等. 并联混合动力汽车能量管理建模及优化研究[J]. 控制工程，2014，21(3)：357-360.
Wang Xin，Li Gao，Zhu Wanli，et al. Modeling and Optimization Simulation on Energy Management of PHEV[J]. Control Engineering of China，2014，21(3)：357-360.