基于模糊神经预测的新型电控液驱车辆的能量管理策略研究

在应用了定压网络液压马达控制系统的车辆上,采用神经模糊预测能量管理控制器。根据研究对象,建立了系统的数学模型并利用MATLAB/SIMULINK工具将其实现。在此预测能量管理策略中,首先应用E lm an神经网络对车辆的负载进行预测;利用预测、当前车辆负载信息以及定压网络的状态对发动机进行控制。采用预测能量管理控制器进行了仿真研究。仿真结果表明预测能量管理策略控制在车辆性能的提升上具有相当的潜力,它使车辆的燃油经济性能提升了1.5%~14.2%。

Predictive Power Management Strategy for Vehicle with Electric Control and Hydrostatic Drive Using Neural Network and Fuzzy Logic

The predictive power management strategy for vehicle with electric control and hydrostatic drive(ECHDV) using neural network and fuzzy logic was adopted.For the new type vehicle,the mathematic model was established and embedded into the MATLAB/SIMULINK to facilitate the evaluation of control strategy.In the predictive power management strategy,Elman neural network was used to forecast the vehicle load information,and based on the predictive,current load information and hydrostatic transmission state,the engine operation control was achieved.By combining the control strategy and model,simulations were carried out.The simulation(results) indicate that the predictive power management strategy shows potential improvement in the fuel economy relative to strategy without predictive information by 1.5%~14.2% in ECHDV.