Modeling and Simulink of Anti-lock Braking System Digital Twin
Implementation Plan
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Step 1: Initially, we Construct a complete ABS Simulink model including wheel dynamics, tire, slip, and controller.
Step 2: Next, we Inject faults such as sensor bias or actuator loss using the Fault Manager subsystem.
Step 3: Then, we simulate and collect data such as time, slip, speed, and torque for analysis and Export as a Dataset.
Step 4: Next, we Extract statistical and spectral features such as mean, RMS, kurtosis, and energy based on collected data.
Step 5: Next, we Train ML models (Random Forest, XGBoost, LSTM) for RUL prediction and fault detection.
Step 6: Finally, we plot the following performance metrics:
6.1: Time vs Wheel Speed (rad/s)
6.2: Time vs Vehicle Speed (m/s)
6.3: Time vs Brake Torque (N·m)
6.4: SHAP Summary Plot (Feature Importance)
6.5: Confusion Metrics(True Vs. Predicted Faults)
Software Requirements:
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1. Development Tool: Matlab-R2023a/Simulink or above and python
2. Operating System: Windows-10 (64-bit) or above
Note:
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1) If the proposed plan does not fully align with your requirements, please provide all necessary details—including steps, parameters, models, and expected outcomes—in advance. Kindly ensure that any missing configurations or specifications are clearly outlined in the plan before confirming.
2) If there’s no built-in solution for what the project needs, we can always turn to reference models, customize our own, different math models or write the code ourselves to fulfil the process.
3) If the plan satisfies your requirement, Please confirm with us.
4) Project based on Simulation only.
5) Here we use Python is only for ML models training progress and plotting(based on collected dataset) not combined with Matlab/simulink model
