Forecasting the Utilization Efficiency of Electric Transport Vehicles in Hot Climate Conditions

Abstract

This article analyzes the main factors affecting the utilization efficiency of electric transport vehicles in hot climate conditions and the issues of forecasting their performance. The operational efficiency of electric transport vehicles is closely related to ambient air temperature, battery state of charge (SOC), driving speed, road conditions, vehicle load level, as well as the energy consumption of air conditioning and other auxiliary electrical systems. A review of the literature shows that under high-temperature conditions, the energy consumed for battery thermal management and passenger compartment cooling can account for a significant share of the vehicle’s total energy consumption. Therefore, assessing the actual operational efficiency of electric transport vehicles solely on the basis of nominal battery capacity or the driving range specified by the manufacturer is insufficient. The article considers physical, statistical, and machine learning approaches to forecasting the energy consumption of electric transport vehicles and proposes a multifactor forecasting model for hot climate conditions. In addition, the possibilities of energy management systems (EMS), vehicle-to-grid (V2G) technology, and the application of end-of-life batteries in secondary energy storage systems are considered. The research results demonstrate the need for an integrated approach to the advance assessment of energy consumption, charging requirements, and operational efficiency of electric buses and electric vehicles under Central Asian conditions.