Development of Fuzzy Logic-Based Lead Acid Battery Management Techniques with Applications to 42V Systems

摘要

As the implementation of 42 volt systems is being phased into commercial vehicles, the battery technology is being developed with little time for adequate long-term testing and modeling to assess battery performance before their implementation into vehicles. Reliable battery monitoring and management systems for these 42 volt systems will be critical for optimizing performance. Furthermore, these battery monitoring and management systems must be developed and implemented rapidly and be adaptable to the changing characteristics of the batteries as they age. Over the last five years, Villanova University and US Nanocorp have been jointly developing patented fuzzy logic-based technology for estimating the state-of-charge (SOC) and state-of-health (SOH) of batteries. This methodology has proven to be both a simple and a powerful means to model battery characteristics accurately and robustly. The methodology can be interfaced to any battery interrogation technique including coulomb counting, voltage recovery, and battery impedance methods. Furthermore, the use of neural network-based algorithms can be used to adaptively modify the fuzzy algorithms based on changing battery conditions. Finally, the fuzzy logic methodology lends itself well to rapid system design and development, and can be implemented efficiently in existing on-board vehicle microprocessors. In this paper, we will describe how impedance measurements and voltage response measurements combined with fuzzy logic data analysis have been used to estimate the SOC of spirally wound 2V lead acid cells. We will also describe how this approach may be extended to 42V battery systems.