%% Battery Management System
% 
% This example shows how to model a battery management system for the state
% of charge estimation. The battery pack comprises of two battery modules,
% which are combinations of cells in series and parallel. The *Battery 
% (Table-Based)* Simscape Electrical(TM) block models each battery cell. 
% In this example, all cells have the same initial temperature and state of 
% charge, but different resistance. The state of each cell is estimated 
% using battery pack current and the measured cell voltages.
% 
% Copyright 2021-2026 The MathWorks, Inc.


%% Model Overview
% This example models a battery pack connected to an auxiliary power load 
% due to the coolant pump. The BMS subsystem defines the required amount of
% the coolant flowrate to cool the high voltage (HV) battery pack. A 
% controlled current source defines the DC current demand from the HV 
% battery pack. To calculate the state of charge for the battery pack, the
% BMS subsystem uses the cell voltages and temperature, and the battery
% pack current. The cell capacity does not change with time or cycling and 
% is the same for all the cells.

open_system('Battery_Management_System')
set_param(find_system(bdroot,'FindAll', 'on','type','annotation','Tag','ModelFeatures'),'Interpreter','off')

%% Battery Cell Overview
% The battery cell is modeled using the equivalent circuit method. You can 
% find the equivalent circuit parameters used for each cell in the 
% |Battery_Management_System_param.m| initialization file . To characterize a 
% lithium-ion cell, this example uses a 1-RC model by setting the |charge dynamics| 
% parameter to |One time-constant dynamics|. This example does not consider 
% cell capacity fade or charge leakage. 

%% Build Battery Pack
% The Battery Pack comprises of 2 series connected Battery Modules. Each 
% module consists of 10 series connected |Pouch| type cells. The value of 
% the terminal resistance, |R0|, in the first cell of the first module is 
% 5% higher than the value of terminal resistance in the other cells. The 
% value of the terminal resistance, |R0|, in the third cell of the second 
% module is 3% lower than the value of |R0| in the other cells. The 
% |Battery_Management_System_param.m| file sets this scenario by specifying
% |iniR01(1,1)| to 1.05 and |iniR02(1,3)| to 0.97.
% 

open_system('Battery_Management_System/Battery Pack')

%% Define Battery Management System
% The BMS subsystem calculates the battery state of charge and controls the
% coolant flowrate. The coolant pump power loss is calculated based on the
% value at the |FlwR| input port, with 500W being the maximum pump power 
% consumption. This example uses the extended Kalman-Filter (EKF) in the 
% SOC estimation subsystem to calculate the state of charge. 

open_system('Battery_Management_System/BMS')

%% Define Battery State-of-Charge Estimation
% To calculate the state of charge, the EKF uses the pack current, cell
% voltages, and temperature data. The SOC estimation subsystem also
% implements a lookup table to define the cell model. The EKF reduces the
% error between the prediction and measurement of the cell voltages.

open_system('Battery_Management_System/BMS/SOC estimation')
 
%% Simulation Results
% This figure shows the simulation results with the parameters defined in
% the |Battery_Management_System_param.m| file. The cell voltages are 
% different for the cells with different resistance |R0|. The BMS accurately 
% tracks the state of charge of all cells.

Battery_Management_System_plot1state 


%%
close all
bdclose all