Efficiency Announcement of Battery EV design by MatLab Intelligent BMS for EVs using Matlab Design and Performance of Smart BMS

Abstract

Fast electrification of road transport has lead to an increasing demand for battery electric vehicles (BEVs) with greater energy efficiency, operational safety, reliability and battery life. The battery pack is one of the most crucial electrical, thermal, and ageing aspects of providing an EV and needs to be highly monitored and managed all the time. Hence, the Battery Management System (BMS) contributes in a crucial way to keeping battery within safe limits and efficient use of available energy. This study introduces the design and performance evaluation of an intelligent BMS structure for Li-ion battery electric vehicle (BEV) with Matlab/Simulink software. The proposed battery configuration is a 4S3P lithium-ion battery system and the proposed framework involves an equivalent-circle nonlinear battery model, State of Charge (SOC) estimation, State of Health (SOH), calculation of electrical losses and thermal modelling and supervisory control. The mathematical expression describes the battery terminal voltage by open-circuit-voltage source, branches of internal resistance and dynamic RC polarisation. SOC is estimated via the current integration with voltage-dependent correction, and SOH is shown in the reported-degradation of-available-capacity. A lumped thermal model is presented, which was used to develop the relationship between electrical losses and battery temperature. The proposed BMS is analyzed using different vehicle operating conditions, such as acceleration, steady-state operation, deceleration. The provided study in MATLAB/Simulink shows stable power delivery, controlled battery operation and reduced electrical losses. It further claims an overall gain in energy efficiency of around 10-15%, as well as thermal stress de-escalation of around 8-12% over the claimed conventional approach. The percentage change improvements, however, need to be verified by cross-checking with the underlying MATLAB numerical outputs as there are no baseline and proposed absolute values in the previous manuscript. It is thus understood as a simulated design and evaluation, rather than experimental proof. Show a comparison between existing battery model and BMS models to clarify the major contribution of the proposed setting is on the combination of nonlinear battery models, state estimation, thermal awareness and adaptive control under a single MATLAB/Simulink environment. Parameters of the battery identified in the experiments should be added for future development in the current model; real driving cycle validation is needed; Hardware-in-the-Loop testing and physical battery experiments should follow prior to practical vehicle deployment.