Supervising MHEV’s control system with GPS data and fuzzy logic to optimize fuel economy

In recent years, the automotive industry requests, even more, the possibility to test the prototyped vehicles on real operating conditions. The integration of sensors and the optimized control strategy have led to more reliable systems. In this paper, a fuzzy logic supervisor to compensate background non-linearities and noises is presented. Authors investigate the resilience of the system using simulations of the full car blocks and the environment reaction. The simulation clearly shows that this controller can maintain excellent performance, can compensate in real-time the noises effect, and can keep the pollutant emission low.