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The Ride Comfort has always been an important attribute of a vehicle that gets trade-off with handling characteristics of a vehicle. However, to cater the growing customer requirements for better ride comfort in a vehicle without compromising on other attributes, evaluating and achieving optimal ride comfort has become a significant process in the vehicle development. In the current engineering capability and virtual engineering simulations, creating an accurate and real time model to predict ride comfort of a vehicle is a challenging task. The qualitative evaluation of ride attributes has always been the proven conventional method to finalize the requirements of a vehicle. However, quantitative evaluation of vehicle ride characteristics benefits in terms of target setting during vehicle development process and in robust validation of the final intended product against its specifications.

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.