• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2017, Vol. 53 ›› Issue (16): 61-69.doi: 10.3901/JME.2017.16.061

• 特邀专栏:汽车先进动力系统的设计、优化与控制(下) • 上一篇    下一篇

基于多工况优化算法的混合电动汽车参数优化

刘永刚1, 李杰1, 秦大同1, 雷贞贞1,2, 解庆波3, 杨阳1   

  1. 1. 重庆大学汽车工程学院 重庆 400044;
    2. 重庆科技学院机械与动力工程学院 重庆 401331;
    3. 比亚迪汽车工业有限公司 深圳 518118
  • 收稿日期:2016-05-24 修回日期:2017-04-20 发布日期:2017-08-20
  • 作者简介:刘永刚,男,1982年出生,博士,副教授,硕士研究生导师。主要研究方向混合动力汽车匹配及其综合控制。E-mail:andyliuyg@cqu.edu.cn
  • 基金资助:
    国家自然科学基金(51575063)、重庆市应用开发计划重大(CSTC2015yykfc60003)和中央高校基本科研业务费(106112016CDJXY330001)资助项目

Parameter Optimization of Hybrid Electric Vehicle Based on Multi-cycle Optimization Algorithm

LIU Yonggang1, LI Jie1, QIN Datong1, LEI Zhenzhen1,2, XIE Qingbo3, YANG Yang1   

  1. 1. School of Automotive Engineering, Chongqing University, Chongqing 400044;
    2. School of Mechanical and Power Engineering, Chongqing University of Science & Technology, Chongqing 401331;
    3. BYD Auto Company Limited, Shenzhen 518118
  • Received:2016-05-24 Revised:2017-04-20 Published:2017-08-20

摘要: 协调优化混合动力电动汽车动力系统与能量控制策略的参数是提高燃油经济性的关键。以汽车的动力性能为约束条件,把电池SOC平衡油耗引入目标函数,提出一种采用模拟退火粒子群算法的基于多工况优化混合动力汽车动力系统与控制策略参数的方法。利用MATLAB/Simulink仿真软件进行建模仿真,结果表明,利用该方法可以获取一组参数,在保持汽车动力性、电池SOC平衡的基础上,相对于优化前,在综合工况下油耗降低了5.49%,分工况HWFET、FTP、LA92、US06_HWY、UDDS与SC03下油耗分别降低了8.46%、4.62%、3.84%、8.43%、5.56%、4.31%。为了证明本方法优化出的参数在其他工况的通用性,选取NEDC工况进行仿真验证,结果发现,在NEDC工况下油耗降低了8.36%。并进行了实车道路试验,试验结果较好的验证了所提出的基本控制策略的有效性。

关键词: 道路试验, 多工况优化, 混合动力汽车, 模拟退火粒子群算法, 能量管理策略

Abstract: Coordinated optimization for parameters of hybrid electrical vehicle (HEV) powertrain and control strategy is the key to improving fuel economy. In order to reduce fuel consumption, a methodology using simulated annealing particle swarm optimization (SAPSO) and multi-cycle is presented to achieve parameter optimization for both the powertrain and the control strategy based on the constraint of the dynamic performance requirements. The simulation have been carried out based on the MATLAB/Simulink software, and the result show that the proposed approach can find a set of control parameters to reduce fuel consumption with keeping power performance and balance of battery SOC. After optimization, the fuel consumption of vehicle will be reduced 5.49% at comprehensive driving cycle and 8.46%, 4.62%, 3.84%, 8.34%, 5.56% and 4.31% at cycles of HWFET, FTP, LA92, US06_HWY, UDDS, SC03, respectively. Without lose generality, the cycle of NEDC have been chose to validate the optimization control parameters and the fuel consumption will be reduced 8.36%. The road test is developed, and demonstrated the effectiveness of the energy management strategy in this work.

Key words: energy management strategy, hybrid electric vehicle (HEV), multi-cycle optimization, road test, SAPSO

中图分类号: