Failure Detection and Battery Management Systems of Lead-Acid Batteries for Micro-Hybrid Vehicles

Pilatowicz, Grzegorz; Sauer, Dirk Uwe (Thesis advisor); Ferg, Ernst (Thesis advisor)

Aachen (2017)
Book, Dissertation / PhD Thesis

In: Aachener Beiträge des ISEA 92
Page(s)/Article-Nr.: 1 Online-Ressource (212 Seiten) : Illustrationen, Diagramme

Dissertation, RWTH Aachen University, 2017

Abstract

Micro-hybrid vehicles (µH) are currently starting to dominate the European market and seize constantly growing share of other leading markets in the world. On the one hand, the additional functionality of µH reduces the CO2 emissions and improves the fuel economy, but, on the other hand, the additional stress imposed on the lead-acid battery reduces significantly its expected service life in comparison to conventional vehicles. Because of that µH require highly accurate battery diagnostics. It is necessary to ensure the vehicle reliability requirements, prolong service life, reduce warranty costs and maximize fuel savings. The latter refers to reducing number of premature engine restarts and missed stop-start opportunities.This thesis presents battery state detection algorithms of lead-acid batteries developed for operation in µH applications. Their novelty is defined by improved accuracy, reliability, robustness and applicability for different types and sizes comparing to the known solutions. It was possible thanks to conducted comprehensive experimental and analytic study, allowing a better understanding of the relevant electrochemical processes. Result of these studies were the foundation for each of the described methods and allowed finding optimal simplifications without significant loss of performance. Reduced complexity is of high importance for implementation of these algorithms into the low-cost hardware, which is responsible for real-time estimation of the battery state, current, voltage and temperature of the terminal as well as communicating these values to the body computer of the vehicle.