Fuzzy control-based system feed-back by OBD-II data acquisition for complementary injection of hydrogen into internal combustion engines

Abstract Since 1996, the California Air Resources Board has established the OBD-II as a communication protocol that systems use to control gas emissions. Such a standard was created in 1988 and allows modern vehicles to obtain technical engine data such as fuel injection, speed, and air mass flow. In this article, an experimental test bench is presented using the Raspberry-Pi 3 programming board and a serial connection to the OBD-II port. Also, the standard ELM327 is employed as a connection adapter to analyze data sets and to calculate the ideal time for hydrogen injection. This process is achieved by an in-situ generator as a supplementary fuel source for internal combustion engines. It permits the reduction of greenhouse gas emissions and improves fuel efficiency, as it has already been reported in multiple previous types of research. The methodology describes the process of acquiring data through the OBD-II port, the type of hydrogen generator, and the calibration implemented according to expert system rules as well as the installation process of the system in the experimental vehicle. The developed algorithm is implemented using the programming language Python to determine the ideal time for activating the hydrogen generator. The results include simulation behavior of the fuzzy logic algorithm in Matlab of vehicle engine for its comparison with the validated results and offer a proposal to optimize hydrogen injection for future researches. Then, the efficiency of electrolyzer in ICE is improved by extending the lifetime of the entire device and the electrolyte.

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