基于MA-ECMS的串联式混合动力拖拉机能量管理策略研究

Study on Energy Management Strategy of Series Hybrid TractorBased on MA-ECMS

能量管理策略的研究则是提高混合动力拖拉机燃油经济性的核心技术问题。本文以后轮轮边驱动的串联式混合动力拖拉机为研究对象,对其混合动力系统构型进行了分析,动力系统主要部件的参数进行了确定,并对不同工作模式的能量流动情况进行了分析;设计了一种基于MA-ECMS的能量管理策略,经过仿真验证,混合动力系统模型具有较好的工况跟随效果;分别设置初始SOC值为0.2、0.6、0.8进行仿真验证,分析不同电池状态下的能量管理效果。结果表明,在不同初始SOC值条件下,能量管理策略均能实现串联式混合动力拖拉机工作模式的准确切换以及动力源功率的合理分配,具有较好的能量管理效果。以初始SOC值为0.6的情况为例,对比了猴群算法优化前后的能量管理策略SOC值变化和燃油消耗情况。优化前ΔSOC为0.0072,百公里燃油消耗量为6.43 L;优化后ΔSOC为0.0009,百公里燃油消耗量为6.11 L。结果表明,优化前后的能量管理策略都能实现SOC的动态平衡,而优化后的SOC动态平衡效果更佳;且经优化后,系统的油耗降低了0.32 L/100 km,节油率为5%,具有更好的燃油经济性。

The study of energy management strategy is the core technical issue to improve the fuel economy of hybrid tractor.In this paper,the tandem hybrid tractor with rear wheel-side drive is taken as the research object,and its hybrid power system configuration is analyzed,the parameters of the main components of the power system are determined,and the energy flow of different operating modes is analyzed;an energy management strategy based on MA-ECMS is designed,and the hybrid power system model is verified to have a better effect of following the working conditions through simulation;The initial SOC values of 0.2,0.6 and 0.8 were set for simulation verification to analyze the energy management effect under different battery states.The results show that under different initial SOC values,the energy management strategies are able to achieve accurate switching of the working mode of the series-connected hybrid tractor and reasonable distribution of the power source power,and have better energy management effects.Taking the case of the initial SOC value of 0.6 as an example,the change of SOC value and fuel consumption of the energy management strategy before and after the optimization of the monkey swarm algorithm are compared.Before optimization,theΔSOC is 0.0072,and the fuel consumption is 6.43 L/100km;after optimization,theΔSOC is 0.0009,and the fuel consumption is 6.11 L/100km.The results show that the energy management strategies before and after optimization can achieve the dynamic balance of the SOC,and the dynamic balance of the SOC after optimization is more effective;and after optimization,the system’s fuel consumption decreases by 0.32 L/100km,and the fuel saving rate is better.100 km,with a fuel saving rate of 5%and better fuel economy.