Model Predictive Control of Regenerative Braking for Hybrid Electric Vehicle Cruising Downhill

Based on the driving states of vehicles equipped with GPS/GIS on board in the future predictive route,a global optimal dynamic programming model of regenerative braking energy recovery for medium hybrid electric vehicle was established.In order to realize a receding horizon optimal control,the global optimal dynamic programming algorithm was converted into a local optimal algorithm within prediction horizon using with the model predictive control method.To overcome the curse of dimensionality of dynamic programming,the rechargeable ranges of SOC and temperature of battery were determined.The calculation comparison among the control strategies of model prediction,global optimization and instantaneous optimization was performed.The simulation under the conditions of different gradients and slope lengths,and cruising downhill was performed.The results show that(1) the computational efficiency of model predictive control strategy is higher than that of global optimal control strategy;(2) energy recovery efficiency of regenerative braking of model predictive control strategy is greater than that of instantaneous optimal control strategies,and not deduce to 1.31% compared with that of global optimal control strategy,the energy recovery is better with shift reminder.