Research on Multidisciplinary Design and Optimization Method of Three-Way Catalytic Converter for Vehicle Gasoline Engine

Taking the flow field, temperature, pressure and stress of the three-way catalytic converter of automotive gasoline engine as the objective constraints, the multi-disciplinary optimization design objective function of the three-way catalytic converter of automotive gasoline engine is established. The flow field simulation, stress field simulation, temperature field simulation and pressure field simulation results of the three-way catalytic converter of automotive gasoline engine are obtained by using the fuzzy neural network. An agent model is established to optimize the proposed adaptive chaotic particle swarm optimization algorithm, and the optimal design parameters of three-way catalytic converter for automotive gasoline engine are obtained. The correctness of the research is verified by experiments.