Energy control method, equipment, storage medium and device based on driving conditions

Abstract

The invention relates to the technical field of hybrid electric vehicles, and discloses an energy control method, equipment, storage medium and device based on driving conditions. The present invention obtains the current driving characteristic information of the hybrid electric vehicle; analyzes the current driving characteristic information to obtain the driving condition category information; determines the preset target relationship function according to the driving condition category information; according to the preset The target relationship function looks up the corresponding target equivalent factor through the preset equivalent factor comparison table; according to the target equivalent factor, the usage ratio information of the engine and the motor in the hybrid vehicle is determined, and the hybrid electric vehicle is realized according to the usage ratio information. The control of vehicle energy, so that the target equivalent factor can be adjusted in real time according to different driving conditions, realizing the instantaneous and global optimization of energy management, and giving full play to the energy-saving potential of PHEV.

Description

technical field [0001] The invention relates to the technical field of hybrid electric vehicles, in particular to an energy control method, equipment, storage medium and device based on driving conditions. Background technique [0002] At present, the plug-in hybrid electric vehicle (Plug-in Hybrid Electric Vehicle, PHEV) energy management strategy includes a rule-based threshold control strategy (Rule-based control strategy, RB), which is mainly based on the designer's engineering experience and various The working characteristics of key power components are designed. The working process of this strategy is based on the steady-state efficiency map of each key power component, the current vehicle speed, the opening of the accelerator pedal, the remaining power (State Of Charge, SOC) value of the power battery, etc. A control variable is used to divide the hybrid system into working modes through a series of fixed thresholds. This strategy has the advantages of simple design...

AI Technical Summary

Problems solved by technology

However, the control threshold of the RB strategy is often a fixed set of thresholds, and the adaptability to working conditions is poor, which may cause the battery power to be "run out" in advance, or the battery power is not fully used at the end of the trip. Both will increase the fuel consumption of parallel PHEVs and worsen fuel economy

[0003] At present, many scholars have proposed PHEV energy consumption strategies based on optimal control theory, such as global optimization dynamic programming algorithm (Dynamic Programming, DP) and Pontryagin's Minimum Principal (PMP), etc., DP control strategy The global optimal solution of the power system control is mainly obtained under the premise of known driving conditions, but it requires a lot of calculations and takes a long time to solve, which leads to the fact that the DP control strategy cannot be directly used in real-time control. PMP The algorithm belongs to the instantaneous optimal control algorithm, which can achieve instantaneous optimal control, but it is not globally optimal when the working conditions change.

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