Vehicle Design Optimization for Minimizing Operating Costs of Electric Vehicles

A technique has been developed which can combine the Peukert, as well as the diffusion based “recovery”, characteristics of a battery pack with a given vehicle design and driving cycle to determine cost of operation. The technique utilizes a mathematical model of the vehicle to determine energy usage, and combines this with a mathematical model of the battery pack to determine apparent depth of discharge (DOD). This technique has been applied using the characteristics of a pasted plate, flooded, lead-acid battery pack and the Federal Urban Driving Schedule (FUDS). The results are compared to test data from the California Air Resources Board (CARB) and the Sacramento Municipal Utility District (SMUD). As lead acid batteries have a cycle life which is strongly related to DOD, it is possible to then relate battery life to the distance driven between charging. This model was run on a wide variety of vehicle types, and the results were used to plot the relationship between cost/mile (both energy and battery replacement) to the number of miles driven between each charge (Depth of Discharge). The curve for any given vehicle has a minimum which falls at 30-40% of the possible driving range for that vehicle. The curves for some vehicles have a well defined minimum, while others have a flat broad shape, corresponding to an insensitivity to variations in the usage patterns. The lack of information regarding drive-train efficiencies in actual usage has lead to the development of an inexpensive data logger for measuring in situ performance, driving cycle requirements and battery pack demands.