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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 CO 2 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 state detection solutions. They are necessary to ensure the vehicle reliability requirements, prolong service life and reduce warranty costs. This paper presents an electrical model based on Butler-Volmer equation. The main novelty of the presented approach is its ability to predict accurately dynamic response of a battery considering a wide range of discharge current rates, state-of-charges and temperatures. Presented approach is fully implementable and adaptable in state-of-the-art low-cost platforms. Additionally, shown results indicate that it is applicable as a supporting tool for state-of-charge and state-of-health estimation and scalable for the different battery technologies and sizes. Validation using both static pulses and dynamic driving profile resulted in average absolute error of 124 mV regarding cranking current rate of 800 A respectively.

In this article, today’s battery technologies and future options are discussed. Batteries have been one of the main focuses of automotive development in the last years. Technologies that have been in use for a very long time, such as the lead–acid battery, are indispensable but need improvement. New technologies such as the lithium-ion battery are entering the market. Supercapacitors (also known as electrochemical double-layer capacitors) can be used for high-power requirements such as regenerative braking. The variety of vehicles has increased with the introduction of hybrid vehicles, plug-in hybrid vehicles and electric vehicles and, for each type, suitable battery types are being used or under development. Appropriate battery system designs and charging strategies are needed. Battery technologies can be classified according to their energy density, their charge and discharge characteristics, system integration and the costs. Further relevant performance parameters are the calendar lifetime, the cycle lifetime, the low- and high-temperature performances and the safety.

Dynamic charge acceptance (DCA) is a key requirement for batteries in micro-hybrid vehicles. In automotive applications, DCA reaches a stable level during several weeks or months in service. A conditioning method that accelerates stabilizing DCA is presented. Various test methods for evaluation of DCA are compared. This is necessary for comparing new technologies (e.g. negative electrodes with carbon additives) and cell concepts (e.g. bi-polar batteries).

SLI lead-acid batteries are still the most commonly used technology in automotive applications around the world. Despite its relatively low gravimetric and volumetric energy density in comparison with other battery solutions it is still installed in the newest micro-hybrid and conventional cars due to its low cost. To facilitate the design of multi-physical systems as complex as modern automobiles, it is critical to have a precise battery aging model that incorporates various operation conditions. This paper presents an aging model that provides crucial information about state of health of SLI battery during lifetime for any conditions like climate, driving style, charging strategy or different battery management approaches. Described model is based both on empirical and physico-chemical solutions and can be calibrated to simulate any SLI lead-acid battery without design limitations.