Modeling and Simulink of Precise Current Sensor Fault Diagnosis in Battery System
Implementation plan:
Step 1: Initially, we will construct a Simulink Model with a 5 phase PMSM Motor.
Step 2: Next, we perform a data collection process.
Step 3: Then, we Preprocess the data using the Adaptive Smooth Variable Structure Filter with a time-varying Boundary Layer (ASVSF-VBL) filter.
Step 4: Next, we implement the Kalman filter and Cuckoo algorithm (KFCA) Equivalent Circuit Model for detecting the current sensor failures.
Step 5: Then, we implement the CNN-LSTM for Fault detection and (Pulse Width Modulation Voltage Source Inverter (PWM VSI) for transistor open circuit failures.
Step 6: Next, we implement the Self-adaptive Bonobo Optimizer with Least Mean square (SaBo – LMS) and Forgetting Factor Recursive Least Squares (FFRLS) algorithm for Monitoring Optimal Problems and Battery Conditions.
Step 7: Finally, we plot performance for the following metrics:
7.1: Time (s) vs. Current (A)
7.2: Time (s) vs. Voltage (V)
7.3: Time (s) vs. State of Charge (%)
7.4: Time (s) vs. Fault diagnosis (%)
7.5: Time (s) vs. Temperature (°C)
7.6: Time (s) vs. Accuracy (%)
7.7: Time (s) vs. Complexity (%)
7.8: Time (s) vs. Convergence rate (%)
Software Requirements:
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1. Development Tool: Matlab-R2023a/Simulink
2. Operating System: Windows-10 (64-bit)
Note: –
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1. We make a simulation based process only, not a real time process.
2. If the above plan does not satisfy your requirement, please provide the processing details, like the above step-by-step.
3. Please note that this implementation plan does not include any further steps after it is put into implementation.
4. If the above plan satisfies your requirement, please confirm us soon.
We implement an existing project
Reference 4: Title:- Current sensor fault diagnosis method based on an improved equivalent circuit battery model
