State of charge of battery planning method for global energy management of hybrid electric vehicles

Abstract

The invention discloses a state of charge of battery planning method for global energy management of hybrid electric vehicles. The method comprises a discrete method of an SOC feasible domain of a vehicle power battery and the planning method of an SOC value, specifically includes a calculation of a corresponding moment of a boundary transition point of the SOC feasible domain, a calculation of aSOC maximum value at each time in the SOC feasible domain, a calculation of the number of discrete points and discrete intervals at each time in the SOC feasible domain, a calculation of the SOC valueunder a corresponding label at each time in the SOC feasible domain and the like. The discrete method achieves reasonable discretization within the feasible domain of a battery SOC based on the limitation of a maximum discrete interval of the SOC and the number of the discrete points of the SOC. The planning method finds an optimal control sequence by planning the SOC value, and achieves global optimality of energy management control. The method both ensures accuracy requirements of battery energy management calculations, and significantly reduces calculation loads and costs, and has high comprehensive performance.

Description

technical field [0001] The invention belongs to the technical field of vehicle energy and battery management, and in particular relates to a battery charge state planning method for global energy management of a hybrid vehicle. Background technique [0002] Facing the increasingly severe energy situation and environmental protection pressure on a global scale, new energy vehicles have become a new growth point in the market. Among them, pure electric vehicles have the advantages of zero pollution and high energy conversion efficiency, but due to the high cost of batteries and low cruising range, the cost performance of pure electric vehicles cannot compete with traditional internal combustion engine vehicles. Hybrid vehicles can give full play to the advantages of internal combustion engine vehicles and electric vehicles, can reduce fuel consumption and increase driving range, and have become a practical solution to energy-saving and environmental protection issues at this s...

AI Technical Summary

Problems solved by technology

[0005] At present, the discretization of the feasible domain of the battery SOC has become a technical problem to be solved. Specifically, when using dynamic programming to solve the optimal control problem in the finite time domain, numerical solutions are often used, and the system state and time must be discretized. , and the system state is mostly vehicle speed and battery SOC, so in the research of hybrid electric vehicle energy management control strategy, the discretization of the feasible domain of battery SOC has become a technical problem that needs to be solved urgently

[0006] In addition, the algorithms related to battery energy management in the prior art have the problems of insufficient precision, complex calculation process, high calculation load, and excessive calculation cost. When applying dynamic algorithms to globally optimize the energy management problem of hybrid electric vehicles, the battery SOC Before discretization, the SOC feasible region is determined according to various influencing factors and constraints. In the existing technology, as the degree of discretization increases, although the optimality increases, the calculation load, calculation efficiency, and calculation cost also increase with the increase of the discretization degree. Therefore, how to reasonably discretize the SOC feasible region and how to obtain a balanced and efficient discretization method has become an urgent problem in the field of power battery energy management

[0007] At the same time, how to obtain the SOC trajectory associated with the minimum fuel consumption has always been a technical problem that needs to be solved urgently in this field. How to apply the dynamic programming algorithm to obtain the SOC trajectory corresponding to the minimum fuel consumption, to a large extent, restricts the comprehensive management level of battery energy and restricts the overall utilization level of hybrid vehicle energy

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