A Black Box Approach to EV Energy Consumption: Integrating Key Parameters for Drive Range Optimization

This paper aims to develop a black box model to improve the accuracy of drive range prediction in electric vehicles. Traditional models are typically based on limited parameters, often overlooking critical factors significantly impacting electric vehicles’ (EVs’) performance and energy consumption. The paper aims to address the gaps in current electric vehicle energy usage models by developing a more comprehensive EV energy consumption model, known as the Black Box Model. The paper incorporates and integrates twenty-three diverse parameters into a single mathematical framework, including conventional factors and auxiliary variables, to positively influence drive range and enhance overall EV performance. The study classifies EVs into eight distinct energy consumption groups, identifying key parameters that lead to sub-optimal drive range predictions. These parameters are systematically incorporated into the model to improve the precision of energy consumption monitoring and drive range estimation. An EV model is created in AVL eSuite and, through simulation, as it plays a critical role in artificial intelligence (AI) workflows by providing a controlled environment, the model was validated using real-world data from Nissan Leaf SV Plus. The model’s results positively demonstrate the role of multi-parameter integration in energy consumption analysis and lay the groundwork for future advancements in optimizing EV drive range, contributing to the broader goal of sustainable and efficient electric mobility.