Energy Management for Low‐Cost and High‐Efficiency of Hybrid Electric Vehicles

Hybrid electric vehicles (HEVs) represent a critical transitional technology toward sustainable transportation, yet the high cost of advanced energy management systems remains a barrier to widespread adoption. This paper challenges the prevailing assumption that high‐performance HEV control requires expensive computing platforms by demonstrating that a well‐calibrated rule‐based energy management strategy (RB‐EMS) implemented on a sub‐$50 Arduino MEGA 2560 microcontroller achieves near‐optimal fuel efficiency. A high‐fidelity MATLAB/Simulink power train model was developed to calibrate control logic, followed by experimental validation on a 1:10 scale functional prototype. Simulation results demonstrate a 38.2% reduction in fuel consumption under the urban dynamometer driving schedule (UDDS) compared to a conventional vehicle (CV; from 6.8 L/100 km to 4.2 L/100 km), maintaining battery state of charge (SoC) within a charge‐sustaining window of 50%–70%. Experimental validation confirms seamless transitions between all operational modes electric vehicle, hybrid power‐assist, and regenerative braking with stable real‐time performance (2.3 ms average control loop execution time). Comparative analysis shows the proposed RB‐EMS achieves 92.7% of the fuel economy improvement of equivalent consumption minimization strategy (ECMS) at only 0.5% of the hardware cost. This work establishes a scalable and cost‐effective paradigm for hybrid vehicle energy management, particularly relevant for emerging markets and educational contexts where affordability is a critical enabler of adoption.