Abstract: This paper proposes an energy management strategy optimization method based on Radau pseudo-spectral method (RPM). The global interpolation polynomial is used to approximate the state variables and control variables in the system. The derivative of the interpolation polynomial approximates the differential equation of the state variables in the dynamic equation. Then the optimal control problem (OCP) is transformed into a nonlinear programming problem (NLP) problem of the variable to be optimized. Taking the battery life model with penalty factor as the objective function, the battery life (the number of battery cycles) in the hybrid energy storage system (HESS) electric vehicle is compared with that with the single battery energy source under the NEDC cycle condition. The results show that the pseudo-spectral optimized HESS can reduce the Ah throughput of the battery pack and reduce the current and power fluctuation range. The battery power and ultracapacitor power have a segmented linear relationship with the required power, and the equivalent life of the battery in the HESS is 25.61% higher than that of the single battery energy source. This paper provides a fast and stable optimization method for the energy management strategy of the HESS, which lays a foundation for matching the optimal system parameters and can be used as an evaluation benchmark for other optimization strategies.

Key words: electric vehicle, hybrid energy storage system, pseudo-spectral method, energy management