• CN：11-2187/TH
• ISSN：0577-6686

• 运载工程 •

### 基于粒子群算法的插电式混合动力客车实时策略*

1. 1. 中通客车控股股份有限公司 聊城 252000；
2. 清华大学汽车安全与节能国家重点实验室 北京 100084
• 出版日期:2017-02-20 发布日期:2017-02-20
• 作者简介:

王钦普，男，1964年出生，研究员。主要研究方向为混合动力汽车能量优化控制。

E-mail：lk--wqp@163.com

李亮(通信作者)，男，1976年出生，博士，副研究员。主要研究方向为汽车动力学与控制。

E-mail：liangl@tsinghua.edu.cn

• 基金资助:
* 国家自然科学基金(51675293， 51605243)和中国博士后科学基金 (2016M590094)资助项目; 20160708收到初稿，20160907收到修改稿;

### Real-time Energy Management Strategy for Plug-in Hybrid Electric Bus on Particle Swarm Optimization Algorithm

WANG Qinpu1, DU Siyu2, LI Liang2, YOU Sixiong2, YANG Chao2

1. 1. Zhongtong Bus Holding Company， Liaocheng 252000；
2. State Key Laboratory of Automotive Safety and Energy， Tsinghua University， Beijing 100084
• Online:2017-02-20 Published:2017-02-20

Abstract:

Plug-in hybrid electric bus (PHEB) has become a hot spot for bus research due to its lower energy consumption and lower emissions, etc. For the complicated and transient driving conditions of city bus, how to minimize the energy consumption of the whole driving cycle by designing the real-time energy management strategy for PHEB is still a problem in the recent years. To solve this problem, an equivalent consumption minimization strategy (ECMS) based on particle swarm optimization (PSO) is proposed. The energy management strategy based on the optimization equivalent factor is proposed. Considering the engine frequently start-up problems at lower vehicle speed, the speed limits for engine start is introduced, and the equivalent factor and the speed of engine start of certain condition is offline optimized by PSO to obtain the PHEB application online real-time strategy. The simulation model of the vehicle is built by Matlab/Simulink. The presented method is verified by simulation and hardware in the loop (HIL) experiments. The results show that, the research strategy could achieve global optimization PHEB approximate energy management strategies under different initial SOCs, the vehicle fuel economy increases by 8.5% comparing with the rule-based strategy.