Eco‐Driving and Energy Management for Connected Hybrid Hub Motor Electric Vehicles: A Hierarchical Approach in Multi‐Signalised Traffic Intersections

ABSTRACT The trend of vehicle electrification has led many auto manufacturers to introduce new electric vehicle models in response to growing market demands for vehicle‐to‐everything (V2X) communication. However, challenges such as range anxiety and rapid battery depletion hinder their widespread adoption and acceptance. This study presents a hierarchical approach based on dynamic programming to effectively address the eco‐driving and energy management issues for connected hybrid hub motor electric vehicles (CHHM‐EVs), which operate with both fuel cells and batteries. The vehicle model and its components were developed in MATLAB and integrated with a traffic control model, utilising traffic data sourced from SUMO software. An optimal solution to the eco‐driving and energy management problem is introduced, divided into several stages to enhance computational efficiency. In the top control layer, an objective function is formulated to plan the desired speed trajectory for navigating multi‐signalised intersections, considering various vehicle and environmental constraints. A complementary cost function in the bottom control layer addresses the operating limits of the battery, fuel cell and hub motors. The proposed methodology was tested across three routes with distinct traffic light timings. The results demonstrate the effectiveness of the approach in optimizing energy savings and power management at consecutive signalised intersections.