An integrated optimization method for dual-motor coupling drive system for electric buses

Abstract

The invention provides an integrated optimization method for a dual-motor coupling drive system for an electric bus, wherein an upper layer and a lower layer algorithm are respectively constructed by using the particle swarm algorithm and the dynamic programming algorithm. Among them, the particle swarm algorithm uses the particle coordinates to represent the system parameters to be optimized, and uses the dynamic programming algorithm as the control strategy optimization algorithm under each particle to optimize the control strategy of the coupled drive system with the system power loss as the objective function. Each particle runs with the optimal control strategy, so that the minimum power loss that the obtained particle can achieve, and the weighted summation of the power loss and the power level is used as the objective function of the particle swarm optimization algorithm, and the particle swarm optimization algorithm seeks its objective function. The particle coordinate corresponding to the minimum value is 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, in particular to the integrated optimization of system parameters and control strategies of the dual-motor coupling drive system. Background technique [0002] The dual-motor coupling drive system is an emerging drive system mainly for large-scale heavy-duty or passenger-carrying electric vehicles with large load and high output power requirements. Its main advantage is that by adjusting the working mode appropriately, 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 structure and system parameters are appropriate will greatly affect the efficiency of the coupling...

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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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