ABSTRACT
Lead acid batteries play a substantial role in portable consumer electronics, electric vehicles and large power energy storage systems. Among the secondary batteries, the lead acid battery has become the mainstream due to its features of having a high energy density, long cycle life, and heavy resistance to corrosion. Because of this, it has been widely applied to portable consumer electronics, electric vehicles, and large power energy storage systems. A good charging method is essential to maximize the usable life span of these batteries. In this paper, a model predictive control-based charging algorithm is proposed to provide a better way to charge these batteries more efficiently.
Battery performance can be improved by introducing a Battery Management System (BMS), which plays a key role in improving the control mechanism of charge and discharge of the batteries as well as monitoring the battery health. A BMS has been designed to maximize the utilization of Deep Cycle batteries. This system controls charging and discharging, protects against overcharge and over discharge, calculates and displays state-of-charge (SOC), and provides safety and temperature control.
This whole project would consist of two segments: software and hardware. The hardware side of this project would need the use of materials such as solar panels, a 12v battery, and a universal programmer, while the software side would necessitate the use of various applications to test, perform fault checks, quality control, and conditioning on the machine built. The BMS can also improve the performance and cycle-life of the battery peak, as well as the reliability and the safety of the electric vehicles.
Developing a working charge algorithm along with a battery management system is the purpose of this project. It will be expected to be capable of analysing the current battery state and manipulating the charge current and voltage flow in order to properly charge the battery to a full state.
Keywords: Deep Cycle batteries, Battery Management System (BMS), Battery performance, working charge algorithm.
