多目标遗传算法的电动汽车电-液复合制动系统控制策略优化  

Multi-objective optimization of the control strategy of EVs electric-hydraulic composite braking system with genetic algorithm

作　　者：张凤娇[1,2] 魏民祥[2] 展益彬 

机构地区：[1]常州工学院机电工程学院,常州213002 [2]南京航空航天大学能源与动力学院,南京210016 [3]上海卓然工程技术有限公司,上海200335

出　　处：《现代制造工程》2015年第7期51-55,60,共6页Modern Manufacturing Engineering

基　　金：国家自然科学基金资助项目(51005133)

摘　　要：控制策略的优化对于电动汽车性能的改善至关重要,电动汽车电-液复合制动控制策略优化的目的是要在满足制动稳定性的前提下尽可能多地回收制动能量。通过引入多目标遗传算法,以制动稳定性及制动能量回收效率为目标,在多个约束条件下对影响电-液复合制动控制策略的多个关键参数进行协同优化,并通过电动汽车再生制动软件仿真平台对优化结果进行了验证。结果表明,优化目标具有很好的收敛性,且优化后的控制策略能够有效提高再生制动能量的回收效率。Optimization of the control strategy plays an important role in improving the performance of electric vehicles. In order to improve the braking stability and recover the braking energy, a Multi-Objective Genetic Algorithm（MOGA） is applied to optimize the key parameters in the control strategy of Electric Vehicles （EVs） electro-hydraulic composite braking system. Various limita- tions are considered in the optimization process and the optimization results are verified by a software simulation platform of elec- tric vehicle regenerative braking system in typical brake conditions. The results show that optimization objectives achieved a good astringency, and the optimized control strategy can increase the brake energy recovery effectively under the condition of ensuring the braking stability.

关 键 词：电-液复合制动 控制策略 遗传算法 多目标优化 

分 类 号：U471.15[机械工程—车辆工程]