Range anxiety is one of the major factors to be dealt with for increasing penetration of EVs in current Automotive market. The major reasons for range anxiety for customers are sparse charging infrastructure availability, unreliable range prediction and uncertain real-world range values. The uncertainty in real world range is due to the variation between the testing condition during vehicle development and real-world customer usage condition.
This paper illustrates a more accurate test methodology development to derive the real-world range in electric vehicles (LMV) with experimental validation and system level analysis. The test methodology developed will be replicating the real-world usage scenario and bridge the gap between testing and Indian customer usage condition. Test conditions are developed based on matrix consisting of different routes, drive modes, Regeneration levels, customer drive behavior, time of drive, locations, ambient conditions etc. Based on the real world customer usage inputs, the route type is divided into Core city, City, 2Lane highway, 4lane highway, Express way, Ghats section, etc., The user input features such as drive, regeneration, etc., are categorized into multiple drive modes and regen levels respectively. Also, other attributes such as AC On/Off condition, different loading condition i.e., Number of passengers/Payload are considered for test matrix definition. A reference vehicle was taken for testing and driven against derived matrix of all routes, drive mode, regen level, time of drive, location combinations. Detailed analysis of the drive data for each major system like Electric powertrain load, HVAC load, Battery Cooling/Heating, Accessory loads, Regeneration, Acceleration etc., is done to understand the individual energy consumption (system wise) under different conditions thereby improving real-world range prediction/correlation.