Open AccessDeveloping a battery monitoring system software in matlab simulink environment using kalman filter
Author(s) -
Alireza Rahighi,
Seyed Mohammad Hadi Seyed Kashani,
Behrang Sakhaee
Publication year - 2019
Publication title -
international journal of applied power engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2624
pISSN - 2252-8792
DOI - 10.11591/ijape.v8.i1.pp1-10
Subject(s) - battery (electricity) , kalman filter , state of charge , lead–acid battery , matlab , software , extended kalman filter , automotive engineering , computer science , engineering , simulation , control engineering , power (physics) , physics , quantum mechanics , artificial intelligence , programming language , operating system
Batteries play a vital role in electrical equipments and electrical engineering tools. In addition, in vehicles, the duties of the battery is very important, both in providing initial start energy for conventional cars and movement energy for electric vehicles. Therefore, the batteries could be counted as one of the most important segments of the electric vehicles. The batteries used in vehicles have various types. The most utilized of which in vehicles are the lead-acid batteries. Due to the noticeable privileges of the lead-acid batteries, they have been widely used in vehicles. The battery of the system, which have been processed in this project, is a traction battery with 24V nominal voltage and 500Ahours nominal capacity. In this project, the Kalman filter method has been used in order to estimate the remaining amount of battery’s charge. Kalman filter is an algorithm that estimates the state of a dynamic system using a set of measurements including fault in a specific time period. Having implemented the Kalman filter to the dynamic model of the battery, an estimation of state of the charge (SOC) and battery parameters have been acquired. This operation was simulated in Matlab Simulink environment and the results of the simulation were compared with the real amounts of the parameters achieved from prior experiments to make sure about the accuracy of the results. In the designed software, a graphical environment has been developed in order to providing an appropriate interface and simplifying the software performance. The program can be easily implemented to a real battery and calculate the desired parameters.