Hybrid power system and energy management method thereof

Abstract

The invention discloses an energy management method of a hybrid power system. The method comprises the steps that signal data needed by energy management strategy calculation is obtained, working condition adaptive calculation is performed on to-be-operated working conditions through a working condition power spectrum self-adaptive algorithm, a corresponding equivalence factor is obtained, the equivalence factor obtained by means of calculation and a working condition equivalence factor in a database are subjected to similarity matching, the needed signal data and the equivalence factors are calculated according to the received energy management strategy, an output power distribution combination is obtained through a whole car energy consumption cost minimum algorithm, adjustment and correction are performed on the output power distribution combination, the output power distribution combination is sent, and output power distribution of each energy source is completed. The invention further discloses the hybrid power system adopting the energy management method.

Description

technical field [0001] The present invention relates to the control technology of the hybrid power system, more specifically, relates to the energy management technology of the hybrid power system. Background technique [0002] Hybrid vehicles are powered by two energy sources, typically an engine powered by fuel and an electric motor powered by electricity. Under the coordinated control of the vehicle energy management system, the dual-energy system cooperates with other components to perform multiple optimized combinations to form different power system working modes to adapt to different driving conditions. [0003] The goal of an energy management strategy is usually a multi-objective nonlinear optimization problem with multiple input variables and constraints, and its control strategy has a significant impact on vehicle dynamics and fuel economy. According to the ideal design goal, the on-board energy storage system (the battery of the power system) should reach a depl...

AI Technical Summary

Problems solved by technology

Although the optimization algorithm of the objective function model of the adaptive control strategy is different, because the adaptive control needs to collect a large amount of power system operating data in real time, calculate the energy consumption, and predict the future working conditions, the optimization process is complicated and the calculation amount is large. The computing power of the current on-board equipment is idle, so it cannot be effectively applied in practice

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