Type-2 Fuzzy Logic Approach for Energy Management of Plug-in Hybrid Electric Vehicle

Plug in Hybrid Electric Vehicles (PHEVs) have garnered attention for their ability to decrease greenhouse gas emissions and reduce reliance on fossil fuels. The effectiveness of energy management strategies is crucial, in optimizing the performance and enhancing the driving experience of PHEVs. When analyzing PHEVs, this study investigates the area of uncertainty and unpredictability within driving conditions and driver behavior. While fuzzy logic control (FLC) relies on inputs and outputs which are vulnerable to uncertainties in real world scenarios. Type two fuzzy logic control (T2-FLC) embraces higher levels of uncertainty by factoring in fuzziness in both input and output variables. As a result, T2-FLC offers adaptable control in dynamic and uncertain settings. A comparative analysis between FLC and T2-FLC applied to a PHEVs energy management system is presented in this paper. The findings indicate that although both FLC and T2-FLC demonstrate energy management capabilities T2-FLC surpasses FLC in handling uncertainties and dynamic variations thereby enhancing energy efficiency and prolonging battery life. T2- FLC exhibits adaptability to changing driving conditions facilitating transitions, between operational modes and optimal utilization of available energy resources. The results of T2-FLC helps to researchers for automotive industry to reduce carbon footprint of environment.