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, limited range of Electric vehicles and range uncertainty due to diverse real-world usage conditions. The uncertainty in real world range can be reduced by increasing the correlation 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 with experimental validation and system level analysis. A test matrix is developed considering several variables influencing vehicle range like 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 modes, 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 the correlation with real-world usage during the product development phase.