Integrated optimization algorithm for dual-motor coupling driving system of electric bus

Abstract

The invention provides an integrated optimization algorithm for a dual-motor coupling driving system of an electric bus. An upper layer algorithm and a lower layer algorithm are respectively constructed by using a particle swarm optimization algorithm and a dynamic programming algorithm. According to the particle swarm optimization, particle coordinates represent to-be-optimized system parameters, the dynamic programming algorithm is used as a control strategy optimization algorithm under each particle, system power loss is used as a target function to optimize a control strategy of the coupling driving system, and it is guaranteed that each particle operates with the optimal control strategy. The obtained particles can reach the minimum power loss, weighted summation is carried out on the power loss and the power level to serve as an objective function of the particle swarm algorithm, and the particle coordinate corresponding to the minimum value of the objective function is sought by the particle swarm algorithm to serve as the optimal system parameter.

Description

technical field [0001] The invention belongs to the technical field of parameter matching of a dual-motor coupling drive system, and in particular relates to the integrated optimization of system parameters and control strategies of a dual-motor coupling drive system. Background technique [0002] Dual-motor coupling drive system is an emerging drive system mainly for large-scale load or passenger electric vehicles with heavy load and high output power requirements. Its main advantage is that it can improve the The load rate of the motor in the entire operating condition, thereby improving the drive efficiency. The dual-motor coupling drive system has a variety of topological structures. Parameters such as motor power and transmission gear ratio play an important role in different topological structures. Whether the topology and system parameters are selected properly will greatly affect the efficiency of the coupling device. play. [0003] The current common parameter mat...

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Problems solved by technology

[0003] The current common parameter matching methods include: matching the motor power and gear transmission ratio according to the vehicle dynamic requirements, and designing the coupling device from the matched parameter value range. This method is the simplest, but does not consider the system parameters. The impact of matching on the efficiency of the coupling device is not suitable for electric buses, which have low requirements on system power and higher requirements on system economy; based on energy management, optimization algorithms are used to match and optimize system parameters. Although this optimization method considers the influence of the coupling device system parameters on the efficiency of the drive system, it does not take into account the influence of the control strategy on the efficiency, which will lead to a large discrepancy between the experimental results and the actual results

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