Online Approximation of SOC and temperature of a electric vehicle by combined OCV-CC method

Abstract

In hybrid electric vehicles parameters, the battery management systems play an important part in state estimation techniques which has to be reliable and precise. A HEV when running checks several parameters constantly to make the control strategies on the upcoming driving conditions. A battery management system consists of various components such as sensors and actuators that helps in the safety of battery, improving the range for driving and helps in cost minimization. A battery management system installed in a HEV assures the vehicle efficiency by estimation of these several parameters and processes the HEV according to it. These parameters are a vital information to the hybrid electric vehicles as this information decoded from the sensors or algorithm provides the update on the vehicle’s component running data. Data such as State of charge, cell’s temperature, state of health of the cell, state of power, state of life, etc. are all taken into the consideration for the running of a hybrid electric vehicles. These parameters are the vital information to the hybrid electric vehicles as this information decoded from the sensors or algorithm provides the update on the vehicle’s component running data. Data such as State of charge, cell’s temperature, state of health of the cell, state of power, state of life, etc. are all taken into the consideration for the operation of a hybrid electric vehicles. In this framework a battery model is planned which is put under direct measurement techniques to successfully estimate State of Charge. These two methods used are OCV method and coulomb counting method technique. A basic thermal model is also projected in this paper to measure temperature of the battery, to verify all these operations, a simulation results has been briefed at last.