In today's vehicles, the rising number of electrical loads presents a challenge to the battery. More than half of the vehicle breakdowns that are caused by the electrical system can be traced back to the lead-acid battery and could have been avoided by knowledge of the battery state. Additionally, new functions of micro hybrid vehicles like start-stop or intelligent alternator control require exact knowledge of the battery state. A BMS (battery management system) provides the necessary information by fast and reliable detection of the SoC (State-of-Charge), State-of-Health (SoH) and SoF (State-of-Function) in terms of cranking capability. So, the BMS is able to minimize the number of vehicle breakdowns due to unforeseen battery failure, to maximize lifetime and efficiency of the battery and to enable CO2 saving functions. The key element of the BMS is an IBS (Intelligent Battery Sensor), which measures battery terminal voltage, -current and -temperature and calculates the battery state. This paper describes the implementation of a BMS using state-of-the-art algorithms for calculation of SoC, SoH and SoF and the efficient implementation of these on Freescale.s IBS for lead-acid batteries. This paper shows the efficient realization of BMS for Micro Hybrid Vehicles using Freescale.s IBS. State-of-the-art algorithms for battery state calculation (SoC, SoH and SoF) are presented. It is shown how special hardware features are used to improve the efficiency of the IBS in terms of power consumption. The use of low-power modes with automated battery state observation (no SW interaction necessary) and sophisticated wake-up mechanisms is presented. As a result, the IBS is able to stay in low power mode for the majority of time. Additionally, through proper HW signal processing, programmable filtering and eased calibration, it is shown that SW complexity is reduced. The principle of fix point math is presented and it is indicated that 16-bit fix point data format is often sufficient for the variables in the BMS algorithms and 32-bit is only sometimes required.


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    Title :

    Efficient management of lead-acid batteries for Micro Hybrid Vehicles


    Contributors:


    Publication date :

    2011


    Size :

    10 Seiten, 4 Bilder, 1 Tabelle, 5 Quellen


    Remarks:

    (nicht paginiert)



    Type of media :

    Conference paper


    Type of material :

    Storage medium


    Language :

    English




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