Heat Loss Calculation of the Electric Drives

In the realm of sustainable public transportation, the integration of intelligent electric bus propulsion systems represents a novel and promising approach to reducing environmental impact—particularly through the mitigation of NOx emissions and overall exhaust pollutants. This emerging technology underscores the growing need for advanced drive control architectures that ensure not only operational safety and reliability but also compliance with increasingly stringent emissions standards. The present article introduces an innovative analysis of energy-optimized dual-drive electric propulsion systems, with a specific focus on their potential for real-world application in emission-conscious urban mobility. A detailed dynamic model of a dual-drive electric bus was developed in MATLAB Simulink, incorporating a Fuzzy Logic-based decision-making algorithm embedded within the Transmission Control Unit (TCU). The proposed control architecture includes a torque-limiting safety strategy designed to prevent motor overspeed conditions, thereby enhancing both efficiency and mechanical integrity. Furthermore, the system architecture enables supervisory override of the Fuzzy Inference System (FIS) during critical scenarios, such as gear-shifting transitions, allowing adaptive control refinement. The study addresses the unique control and coordination challenges inherent in dual-drive systems, particularly in relation to optimizing gear selection for reduced energy consumption and emissions. Key areas of investigation include maximizing efficiency along the motor torque–speed characteristic, maintaining vehicular dynamic stability, and minimizing thermally induced performance degradation. The thermal modeling approach is grounded in integral formulations capturing major loss contributors including copper, iron, and mechanical losses while also evaluating convective heat transfer mechanisms to improve cooling effectiveness. These insights confirm that advanced thermal management is not only vital for performance optimization but also plays a central role in supporting long-term strategies for emission reduction and clean, efficient public transportation.