Non-linear model prediction control method for double planetary gear row type hybrid electric vehicle

Abstract

The invention provides a non-linear model prediction control method for a double planetary gear row type hybrid electric vehicle. According to the method, based on the predicted rotation speed of the finished vehicle and the torque requirement, optimization solution is conducted on an objective function during the prediction time interval through a non-linear optimization algorithm, the optimal control sequence of controlled quantities is obtained, and the required torques of a power system engine, a motor, a power generator and a brake system are determined by combining the first controlled quantity of the control sequence with kinetic equations of the double planetary gear row type hybrid electric vehicle in various modes. According to the characteristic that the number of working modes of the double planetary gear row type hybrid electric vehicle is large, control prediction and optimization are achieved through a non-linear model, the combination and disconnection states of all clutches and braking force in a power coupling mechanism can be effectively controlled, optimization of the different working modes and optimal energy distribution among different power components are achieved, and the advantage that the number of the working modes of the double planetary gear row type hybrid electric vehicle is large is brought into full play.

Description

technical field [0001] The invention relates to a real-time optimization method for energy management of a hybrid electric vehicle, in particular to a nonlinear model predictive control method for a dual-planetary hybrid electric vehicle. Background technique [0002] With the aggravation of the global energy crisis and environmental pollution, the development of new energy vehicles has become one of the development themes of the automotive industry today. Compared with pure electric vehicles, hybrid vehicles can guarantee higher power and mileage due to the engine system of traditional vehicles. The hybrid electric vehicle effectively improves the working efficiency of the engine and reduces the fuel consumption of the whole vehicle. At present, dual-planetary hybrid vehicles with more modes have been developed rapidly. Due to the use of dual-planetary power coupling mechanisms and the introduction of clutches, brakes and other means, dual-planetary hybrid vehicles are com...

AI Technical Summary

Problems solved by technology

[0003] At present, the energy management strategies commonly used in hybrid electric vehicle applications are mainly rule-based control strategies, but their design objectives are single, and they cannot be applied to flexible control of multiple working conditions and driving conditions. Although the control strategy based on the global optimization algorithm can obtain global Optimal control sequence, but its large amount of calculation cannot meet the real-time control requirements of hybrid electric vehicles, and its solution must be based on known operating conditions, which also limits the practical application of the global optimization algorithm

The control algorithm based on instantaneous optimization can meet the real-time control requirements of hybrid electric vehicles, and has been well applied at present, but its control parameters are still greatly affected by the working conditions, and its control effect needs to be further improved

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