摘要
为解决多能量源电传动系统的供能任务分配与管理问题,以能量管理控制策略为研究目标,结合理论分析与实验数据建立了面向实时控制的电传动系统Simulink模型。根据系统工作特点,提出了一种"功率跟随+恒温器"与模糊控制相结合的能量管理策略。为了进一步提升电传动系统燃油经济性,基于差分进化理论提出了一种混合粒子群优化算法(DEHPSO),并结合算法对功率跟随控制策略的转速切换值进行了优化。仿真结果表明:设计策略实现了供能任务的合理分配,使系统具备了较高的工作效率和功率输出能力。通过DEHPSO算法优化后,系统燃油消耗降低了8.27%,燃油经济性得到了进一步提高,为改善电传动系统综合工作性能提供了有效途径。
Aiming at the problem of power distribution and management of multi-source electric drive system,the power management control strategy was investigated. Combined with theoretical analysis and experimental data,real-time control oriented Simulink models of electric drive system were established. According to the working characteristics of system,a novel power management control strategy which combined with'power-following and thermostat'and fuzzy theory was proposed. In order to improve the fuel economy,a hybrid particle swarm optimization algorithm based on differential evolution theory was put forward and the value of switching speed point of power-following control strategy was optimized. The simulation results indicate that the designed strategy obtained good effects on power management,which achieved high working efficiency and power output capacity. Optimized by DEHPSO algorithm,fuel consumption of the system is reduced by 8.27% and the fuel economy is obviously improved,which will offer an effective way to improve integrated performance of electric drive system.
出处
《电气传动》
北大核心
2016年第1期3-9,共7页
Electric Drive
基金
国家自然科学基金(51175511)
关键词
电传动
能量管理
粒子群优化算法
差分进化理论
electric drive
power management
particle swarm optimization algorithm
differential evolution theory
