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EV Battery Pack Life: Pack Degradation and Solutions

Authors: Blake E. Dickinson; David H. Swan;

EV Battery Pack Life: Pack Degradation and Solutions

Abstract

<div class="htmlview paragraph">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.</div> <div class="htmlview paragraph">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.</div> <div class="htmlview paragraph">The results of these experiments should help electric vehicle and battery manufacturers understand and design battery management systems that will reduce pack degradation. It is the feelings of the authors that the Battery Management System (BMS) must be able to <u>prevent</u> module damage and pack capacity imbalance. We do not feel that a BMS system can fix damaged modules. Further, the system must be reactive to prevent damage and to be able to accept replacement modules. The system must be flexible (programmable) and have the ability to learn about the pack. The BMS must be able to interface with proper chargers (high power) and inverters/controllers; optimally it would be best to integrate the inverter, charger and BMS. The BMS should provide driver and maintenance information such as: State of Charge (SOC) and range available, bad modules and module temperature.</div>

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Top 10%
Average
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