Fuzzy logic based optimal power flow management in parallel hybrid electric vehicles

Abstract—Parallel Hybrid Electric Vehicle powertrain (PHEV), combining an electric motor with an auxiliary power unit, improves vehicle performance and fuel economy, reducing the effects of private cars on air quality in cities. These advantages can be enhanced by using a dedicated control strategy to identify the optimal power flow distribution at each instant of time in the main powerdrive sources as a function of the state of the powerdrive components and the actual driving conditions. In this connection the literature analysis has evidenced as the research efforts in the field of PHEV optimal power flow management should be oriented not only to develop precise and robust control strategies that can improve the vehicle performances, but also to lower the required computational resources making the solution strategy suitable with the vehicle dynamics and allowing, moreover, a cost effective hardware implementation. To develop this complex activity, fuzzy logic (FL) was used. As demonstrated by the simulation studies developed, FL enables the optimal power flow management problem to be solved by handling its intrinsic non-linearity using rules, membership functions, and the inference process. This results in improved performance, simpler implementation, and reduced design costs compared with rigorous mathematics based approaches