Abstract
The estimation of vehicle battery performance is typically addressed by testing the battery under specific operation conditions by using a model to represent the test results. Approaches for representing test results range from simple statistical models to neural networks to complex, physics-based models. Basing the model on test data could be problematical when testing becomes impractical with many years life time tests. So, real time estimation of battery performance, an important problem in automotive applications, falls into this area. In vehicles it is important to know the state of charge of the batteries in order to prevent vehicle stranding and to ensure that the full range of the vehicle operation is exploited.
In this paper, several battery models have studied including analytical, electrical circuits, stochastic and electro-chemical models. Valve Regulated Lead Acid “VRLA” battery has been modelled using electric circuit technique. This model is considered in the proposed Battery Monitoring System “BMS”. The proposed BMS includes data acquisition, data analysis and prediction of battery performance under a hypothetical future loads. Based on these criteria, a microprocessor based BMS prototype had been built and tested in automotive Lab, Helwan university. The tests show promising results that can be used in industrial applications
Keywords: Battery, Modelling, Simulation, Fault diagnosis, VRLA.