Fuzzy neural network is an intelligent method based on state feedback. In the process of learning and recognition, it has a very high fault tolerance rate and can help people quickly and accurately find the information they need. The engine idle speed and fuel combustion process are measured by using the fuzzy neural network control method. Therefore, in order to improve the idle speed control ability of gasoline engine, this paper studies the application of fuzzy neural network in its control system. This paper mainly uses the experimental method to compare and analyze the fuel economy based on multi-mode through the variables of vehicle idle parking in different periods. The experimental results show that the fuel economy of the start stop system in peak hours is increased by 20.38% on average. The idle start stop control strategy based on multi-mode information can effectively improve the fuel economy of the start stop system.

Logesh Velmurugan. Idle Speed Control of Gasoline Engine Based on Fuzzy Neural Network. Kinetic Mechanical Engineering (2021), Vol. 2, Issue 4: 49-57. https://doi.org/10.38007/KME.2021.020406.

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