Study on the Rule-based Control Strategy for PHEV According to Two-state Dynamic Programming Algorithm - Wei Hanbing; Zhu Ning (Jixie chuandong)
Comprehensive optimization of fuel economy and emissions of diesel engine hybrid plug-in electric vehicle has been investigated. A vehicle dynamic model considering Selective Catalytic Reduction（ SCR） aftertreatment system is established on MATLAB/Simulink simulation platform. A multi-objective optimization function with fuel consumption and SCR outlet’s NOxemission is developed by adopting two states dynamic programming algorithm to solve global optimization problem. Specifically,the battery SOC and SCR temperature is designated as two states respectively which reflect the powertrain system and aftertreatment system dynamics. Based on the optimized results,a rule-based control strategy which is applicable for real-time control is deduced. Compared with CS-CD control strategy,the simulation result shows the fuel economy and NOx emission both is decreased by 1. 9% and 9. 3%.