Project 2
Li-ion Battery System Design in EV & ES Project-2
1.Using MATLAB/simulink and the drive cycle from the attached excel sheet, find-
A.The max heat generation of the battery
B.The SOC of the battery at 2 *104second of the battery operation
Time Time Step Battery Current
00:00.4 0.1 -0.9632
00:00.5 0.2 -0.952
00:00.6 0.3 -0.9072
00:00.7 0.4 -0.9632
00:00.8 0.5 -1.0304
00:00.9 0.6 -0.9632
00:01.0 0.7 -1.0304
00:01.1 0.8 -1.008
00:01.2 0.9 -0.9856
00:01.3 1 -0.9632
00:01.4 1.1 -0.9184
00:01.5 1.2 -0.9296
00:01.6 1.3 -0.9296
00:01.7 1.4 -0.9296
00:01.8 1.5 -0.9184
00:01.9 1.6 -0.9408
00:02.0 1.7 -0.896
00:02.1 1.8 -0.9072
00:02.2 1.9 -0.9072
00:02.3 2 -0.9408
00:02.4 2.1 -0.9296
00:02.5 2.2 -0.9296
00:02.6 2.3 -0.9968
00:02.7 2.4 -0.9968
00:02.8 2.5 -0.9408
00:02.9 2.6 -0.9408
Battery resistance is 2milliohm
Consider the battery resistance is 0.5 mOhm, delta time is 0.1 and entropic factor is 2Ans:
Aim of the project:
A.To perform Thermal Analysis of Battery Under Drive Cycle
During both charging and discharging, batteries generate heat due to enthalpy changes, electrochemical polarization, and internal resistive losses. Uneven heat distribution can cause inconsistencies in the charge/discharge behavior of cells in a battery pack, potentially resulting in thermal runaway, which can lead to fire or explosion if not properly managed.
Peak Current Observation:
- Maximum current from the drive cycle: −0.896 A at 120 seconds
Internal Resistance:
- Resistance of the battery: 0.5 milliohm
Joule Heating Calculation:
Q_joule = I^2 × R × t = (-0.896)^2 × 0.5 × 120 = 48.16 mJ
Entropic Heat Contribution:
- Assumed entropic heat: 2 mJ
Total Maximum Heat Generated:
Result : Total maximum heat generated: Q_total = Q_joule + Q_entropic = 48.16 + 2 = 50.16 mJ
B.To provide Simulink Model for State of Charge (SoC) Estimation
State of Charge (SoC) indicates the remaining charge in the battery, similar to a fuel gauge. It is expressed as a percentage of the full battery capacity.
100% SoC = Fully charged
0% SoC = Fully discharged
Importance of SoC Estimation:
- Prevents overcharging/discharging
- Improves battery reliability and lifespan
- Enhances Battery Management System (BMS) performance
- Ensures safety and energy optimization
SoC Basic Formula: SoC_t = Q_t / Q_n
SoC Estimation Methods
A. Voltage-Based Method
Maps the battery's terminal voltage to SoC using the predefined voltage vs. SoC discharge curve.
Challenges:
- Voltage fluctuations
- Cell chemistry variations
- Measurement noise
B. Coulomb Counting Method
This method integrates the battery's current over time:
SoC(t) = SoC(t-1) - (I(t) × Δt) / Q_n
Limitations:
- Accumulates error over time
- Sensitive to current noise, temperature, and aging
- Requires known initial SoC
C.Modified Coulomb Counting Method
Enhanced with corrected current based on a quadratic relationship:
I_corrected = k2 × I^2 + k1 × I + k0
SoC(t) = SoC(t-1) - (I_corrected(t) × Δt) / Q_n
Result: Improved SoC accuracy in dynamic environments.
Model Components:
-1. Battery Block
Function: Simulates a rechargeable battery by modeling its electrical characteristics based on its state of charge (SoC), voltage, and internal resistance.
Key Parameters:
Nominal voltage: Voltage at full charge under nominal load.
Rated capacity (Ah): Total charge the battery can deliver.
Initial SoC: Battery's starting state of charge.
Internal resistance: Models the voltage drop inside the battery.
Purpose in Model: Acts as the main power source; its response to load (current drawn or supplied) determines voltage and SoC changes.
(Figure 1: Battery block parameters)
(Figure 2: Battery block discharge parameters)
2. Controlled Current Source
Function: Provides a current based on an input signal.
Key Parameters:
Input signal: Controls the magnitude of the current supplied or absorbed.
Purpose in Model: Simulates real-world current loads or charging behavior, typically driven by drive cycle input from Signal Builder.
3. Signal Editor (Drive Cycle Input)
Function: Allows you to define, import, and simulate time-based input signals such as vehicle speed or load current over time.
Key Features:
Supports multiple signals.
Can import data from Excel or MAT files.
Graphical editing of input waveforms.
Purpose in Model: Provides a realistic time-series current profile (e.g., from a drive cycle) to control the Controlled Current Source.
(Figure 3: Signal editor block parameters representing current cycle input)
4. Resistor
Function: Models a physical resistor, dissipating energy and affecting voltage drop.
Key Parameters:
Resistance (Ohms): Defines the voltage drop for a given current.
Purpose in Model: Represents internal resistance or contact resistance in the circuit. Ensures realism in voltage behavior under load.
5. Bus Selector
Function: Extracts specific signals from a bus (grouped signals) and routes them to other blocks like scopes or displays.
Use Case:
Select SOC, Current, and Voltage from the Battery block’s output.
Purpose in Model: Helps isolate and display key battery parameters for analysis.
6. Scope
Function: Displays simulation signals over time (like an oscilloscope).
Features:
Multiple input signals can be displayed in one or more axes.
Supports zooming, cursors, and data export.
Purpose in Model: Used to visualize how SoC, current, and voltage change over time in response to the drive cycle input.
Drive Cycle Import:
1. Open Signal Builder
2. File → Import File
3. Select Excel file
4. Confirm and apply
Model Explanation:
- Connect signal builder to controlled current source
- Connect source to battery via resistor
- Extract SoC, current, and voltage using Bus Selector
- Visualize on Scope
(Figure 4: Simulink model to determine SOC of the battery)
Observations & Results :
- Current is negative: battery in charging mode
- SoC rises 50 % to 51.5%
- Voltage increases from 3.6 V to 3.9 V
- Current matches drive cycle
(Figure 5: Results: SOC(%), Current(A), Voltage(V) of the battery )
(Figures, Model, results, observations are mentioned in the attached document)