基于模型预测控制的混合动力汽车下坡再生制动策略  

Regenerative Braking Strategy for Hybrid Electric Vehicles in Downhill Driving Based on Model Predictive Control

作　　者：舒红[1] 郑军[1] 胡明辉[1] 梁元波[1] 

机构地区：[1]重庆大学,机械传动国家重点实验室,重庆400044

出　　处：《汽车工程》2013年第9期775-780,共6页Automotive Engineering

基　　金：国家自然科学基金(61074062)资助

摘　　要：为了充分回收汽车下坡再生制动能量,并保证蓄电池循环寿命,在对汽车匀速下坡再生制动全局优化控制策略分析的基础上,提出以再生制动能量回收最大和蓄电池温升变化率最小为双目标的混合动力汽车匀速下坡再生制动模型预测控制策略。对不同坡长、不同坡度的匀速下坡工况进行仿真的结果表明:模型预测控制策略在再生制动能量回收率、蓄电池温升和充电速率方面都获得良好的控制效果,且计算效率高,满足实时控制要求。In order to fully recover the downhill regenerative braking energy of vehicles and maintain battery cycle life, and based on the analysis on the global optimal control strategy of regenerative braking energy of vehicles in cruising downhill, a model predictive control strategy of regenerative braking model for hybrid electric vehicle cruising downhill is proposed with maximizing regenerative braking energy and minimizing battery temperature rising rate as bi-objectives. The results of cruising downhill simulation at different slope lengths and gradients show that the model predictive control strategy achieves good control effects in terms of recovery rate of braking energy and the temperature rise and charging rate of battery, with higher computing efficiency, meeting the requirements of real-

关 键 词：混合动力汽车 模型预测控制 再生制动 蓄电池温度 动态规划 

分 类 号：U461[机械工程—车辆工程]