Study On The Instantaneous Optimization Control Strategy Of HEVs

Without the limitation of the battery life in electric vehicles (EVs), the cruising range of HEVs can be much longer; also, unlike conventional vehicles, which are powered by internal combustion engines, the fuel efficiency of HEVs are much higher. Therefore, with the growing shortage of energy, HEVs are getting more and more popular. In general, a HEV has two different sources of power to move a HEV, an electric motor (EM) and an internal combustion engine (ICE), so it needs an energy control strategy to decide how the power needed by the vehicles should be distributed between EM and ICE, which determines the performance of the vehicle. So, this thesis regards the energy control strategy of a single-axle parallel hybrid vehicle as the object of research, which aims to improve the fuel economy.Firstly, the simulation model of a single-axle parallel hybrid vehicle is built by the ADVIOSR software, and the introduction of the engine, motor, and battery mode are presented in detail. Then, to obtain the optimal solution to the energy control problem of the hybrid power system, the dynamic programming method (DP) is applied. During the application of DP, the characteristics of the hybrid system are fully considered to reduce the state variable’s discrete magnitude at each time step, which can improve the speed of calculation, so the optimal control results of the hybrid vehicle over long distance driving cycle could be obtained.Then, the equivalent consumption minimization strategy (ECMS) is introduced, and though the simulation using the ECMS with steady equivalent factor, the effect of the equivalent factor is studied and its effective range determined. Based on the optimal control results obtained through DP, a method is designed to get the optimal equivalent factor at every time step, which assumes that the optimal control results was obtained by ECMS and calculates the equivalent factor needed to get the same result with DP’s, and this equivalent factor is defined as the optimal one in this thesis. After that, the distribution characteristics of the equivalent factor is studied, and the fitting relationships between the mean value of the equivalent factor and the maintained value of the state of charge (SOC) is obtained. Also, through the simulation of the vehicle model on different SOC level using DP as the energy management strategy, SOC’s best working range of the battery is determined.Finally, based on the conclusion obtained above, a new energy control strategy, adaptive equivalent consumption minimization strategy (A-ECMS), is designed, which changes the value of the equivalent factor based on the SOC at that time and aims to confine SOC to the best range of it. Following closely, the effect of the new A-ECMS strategy is verified through the simulation over different driving cycles, which shows that the new A-ECMS designed could get excellent control effect and has a good adaptability.