Noriyasu Iwane, Taiji Mitsuyama, Yudai Tanimura
Abstract
Recently, the lead-acid battery state sensor integrated vehicles have been proliferating. We, as the only single Japanese supplier of the battery state sensor, are working hard for addressing various technical requirements from automobile manufacturers, aiming at increasing our market share of the battery sensors even further. The background, in which the lead-acid battery state sensor integrated vehicles has been increasing, indicates the strong demand for a higher reliability for vehicle power system. On the other hand, the variation of batteries themselves has also increased even further as special batteries have been developed, which can stand the severe operating environment required in the mild hybrid system integrated vehicles. As a part of this technical trend, automotive manufacturers have been expecting us to develop a technology to identify special battery types for mild hybrid vehicles from normal lead-acid types. We have developed the identification technology mentioned above based on using both the equivalent circuit model learning technology which we have been developing and the Support Vector Machine jointly which, they say, is the strongest tool among current identification tools. Further, we have confirmed the good possibility sufficient for practical applications as a result of our trials.
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