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Several lead-acid battery packs of different manufacture and voltage were evaluated on a performance and life-cycle basis. The battery packs ranged from a small 36 volt laboratory pack to a 320 volt full size U.S. Electricar S-10 truck pack. The influence of the charge algorithm, ambient temperature, and module connection methods for parallel strings on the performance and cycle-life of this laboratory pack was studied. Finally, a survey of presently employed battery management techniques, used in three “production” electric vehicles, was conducted. A standard set of testing procedures for electric vehicle batteries, based on industry accepted testing procedures, were used in the evaluations. The battery packs were evaluated by a combination of constant current capacity tests, cyclical loading to simulate typical EV driving cycles and actual EV driving experience.

The zinc bromine battery is a high energy density sealed battery that utilizes a flowing electrolyte and low cost materials (predominantly plastic) and operates at ambient temperatures. The typical full scale specific energy for this bipolar plate battery is more then twice that of lead acid batteries. The engineering research presented in this paper is the design and construction of a high-voltage, zinc bromine battery for use in an electric vehicle. Specifically, a 390 volt system is being integrated into a US Electricar S10 light-duty truck. The research goal is to show a reliable and practical electrochemical power system that is lighter and provides a longer range and shorter recharge times than lead acid batteries. Results of this study will help determine the applicability and practicality of zinc bromine technology for electric vehicles.

Battery technologies of different chemistries, manufacture and geometry were evaluated as candidates for use in Electric Vehicles (EV). The candidate batteries that were evaluated include four single cell and seven multi-cell modules representing four technologies; Lead-Acid, Nickel-Cadmium, Nickel-Metal Hydride and Zinc-Bromide. A standard set of testing procedures for electric vehicle batteries, based on industry accepted testing procedures, and any tests which were specific to individual battery types were used in the evaluations. The batteries were evaluated by conducting performance tests, and by subjecting them to cyclical loading, using a computer controlled charge - discharge cycler, to simulate typical EV driving cycles. Criteria for comparison of batteries were: performance, projected vehicle range, cost, and applicability to various types of EVs. The four battery technologies have individual strengths and weaknesses and each is suited to fill a particular application.

Neural networking is a new approach to modeling batteries for electric vehicle applications. This modeling technique is much less complex than a first principles model but can consider more parameters than classic empirical modeling. Test data indicates that individual cell size, geometry, and operating conditions affect battery performance (energy density, power density and life). Given sufficient experimental data, system parameters, and operating conditions, a neural network model could be used to interpolate and perhaps even extrapolate battery performance under wide variety of operating conditions. As a result, the method could be a valuable design tool for electric vehicle battery design and application. This paper describes the on going modeling method at Texas A&M University and presents preliminary results of a tubular lead acid battery model.