Abstract
To ensure a reasonable energy distribution of multiple energy sources of extended-range electric vehicles in different driving scenarios, this paper proposes an adaptive energy management strategy optimization based on different road slope information and conducts in-depth real-time applications. Aiming at the problem of searching for the best working curve of APU, the method of cubic polynomial is used to obtain the efficiency curve of the range extender under the same speed and torque distribution from the experimental efficiency curves of the engine and generator, and then the golden section method is used to calculate the best working curve of APU and Search for the best working point. Taking the equivalent fuel consumption as the fuel economy index, the improved genetic algorithm is used to optimize the parameters of the energy management strategy under different working conditions and different road gradient information. Under the C - WTVC and CHTC - HT cycle conditions, the fuel economy simulation of logistics vehicles with different road gradient information is carried out. The simulation results show that: under different conditions and different road gradient information, the automatic adaptive energy management strategy can effectively improve the fuel economy performance, control the SOC fluctuation of the power battery well, and improve the battery life.
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