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Three-way catalyst (TWC) converters are often used to purify toxic substances contained in exhaust emissions from gasoline engines. However, a large amount of CO, NOx and THC may be emitted before the TWC reaches its light-off temperature during a cold start. In this work, a numerical model was developed for studying the purification performance of a close-coupled TWC converter during the cold start period. The TWC model was built using axisuite, commercial software by Exothermia S.A. Model gas experiments were designed for calibrating the chemical reaction scheme and corresponding reaction rate parameters in the TWC model. The TWC model was able to simulate the purification performance of CO, NOx and THC under both lean and rich air-fuel equivalence ratios (λ) for different conditions. The light-off temperature and oxygen storage capacity (OSC) behavior were also successfully validated in the model. Vehicle tests were conducted on a chassis dynamometer to verify the TWC model.

For a series hybrid electric vehicle (SHEV), the electric motor is responsible for driving the wheels, while the engine drives the only generator to provide electricity. SHEVs set a control strategy to make the engine run near the fixed operating point with high thermal efficiency, thereby effectively reducing fuel consumption. The powertrain system of HEV is more complex than that of a conventional drive system using only an internal combustion engine, and it is time-consuming to obtain the optimal components specification values and control parameters. Therefore, automatic optimization methods are required nowadays. We used Genetic Algorithm (GA) as the optimization method and optimize powertrain specifications and control parameter values to reduce fuel consumption. The results show that it is an effective optimization method.