“Battery Monitoring for State-of-Charge and Power optimization using LabVIEW” Mrs. Sarita Chauhan 1 , Ashish Sharma 2 and P ratiti Sharma 3 ABSTRACT: As the transportation industry strives to electrify their vehicles, the onboard power source remains a weak link. Fuel cells and secondary batteries are often considered major candidates for providing the primary motive power or serving as load- leveling devices. Due to the relative maturity of the secondary batteries, much effort by academia and industry is devoted to making batteries re- liable and affordable for the electrification of vehicles. In addition to the development of new batteries with better capacity and power capabil- ity, an advanced battery management system is also required to better utilize the capacity of the batteries and to provide diagnostic information for the benefit of the driver. Unfortunately, the internal battery states such as energy remaining are not readily available for direct monitoring. The development of a battery monitoring system that accurately estimates the internal states from available external measurements such as voltage and current is thus important. Therefore, here we present a project dealing with the cause aforesaid. In this we shall implement a method to determine the battery state of charge. Battery state of health and state of Function will also be determined as pre-requisites for the purpose. This project uses system identification techniques to implement a monitoring system for lead-acid batteries in an electric vehicle. Specifically, the information that the proposed methodology provides can help estimate the energy remained in the battery bank (State of-Charge (SOC)) and the power capability of the battery bank (State-of-Function (SOF)).Software requirements will be LabVIEW for the Graphical User Interface. keyword: LabVIEW 1. INTRODUCTION With the development of new batteries with better capac- ity and power capability, an advanced battery manage- ment system is also required to better utilize the capacity of the batteries and to provide diagnostic information for the benefit of the driver. Unfortunately, the internal bat- tery states such as energy remaining are not readily avail- able for direct monitoring. The development of a battery monitoring system that accurately estimates the internal states from available external measurements such as volt- age and current is thus important. Most secondary bat- teries have thin, cylindrical strips for their electrodes. The cylindrical strips are rolled with a separator between the electrode strips and then placed in a cylindrical can. This design tends to achieve a higher electrode surface area that increases the battery power density while lowering the en- ergy capacity due to the increased size of current collector needed to support the electrode . The lead-acid battery technology generally suffers little or no memory effect . Memory effect refers to the restricted capacity that some batteries exhibit when they have been subjected to a par- ticular limited range of capacity use. The lack of memory effect makes this technology a strong candidate for back- up power applications. Lead-acid batteries, however, suf- fer from a relatively low energy density and irreversible capacity loss during deep discharge. 2. Background Work As the transportation industry strives to electrify their vehicles, the onboard power source remains a weak link. Fuel cells and secondary batteries are often considered ma- jor candidates for providing the primary motive power or serving as load-leveling devices. Due to the relative matu- rity of the secondary batteries, much effort by academia and industry is devoted to making batteries reliable and affordable for the electrification of vehicles. In addition to the development of new batteries with better capacity and power capability, an advanced battery management system is also required to better utilize the capacity of the batteries and to provide diagnostic information for the benefit of the driver. Unfortunately, the internal battery states such as energy remaining are not readily available for direct monitoring. The development of a battery moni- toring system that accurately estimates the internal states from available external measurements such as voltage and current is thus important. 3. The State-of-the-Art Review On studying this chapter we can say SOF online es- timation is based on the information obtained from recent voltage and current measurements. Means if the impedance can be known and the OCV can be treated as constant for the short span of time period then the power capability of the battery can be predicted. The Peukert modification approach attempts to estimate useful energy, thus taking into account SOF, for static 2405 International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 4, April - 2013 ISSN: 2278-0181 www.ijert.org