Battery State-of-Charge Estimation

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This example shows how to estimate the battery state of charge (SOC) by using a Kalman filter. The initial SOC of the battery is equal to 0.5. The estimator uses an initial condition for the SOC equal to 0.8. The battery keeps charging and discharging for 6 hours. The extended Kalman filter estimator converges to the real value of the SOC in less than 10 minutes and then follows the real SOC value. To use a different Kalman filter implementation, in the SOC Estimator (Kalman Filter) block, set the Filter type parameter to the desired value.

To learn more about the SOC, battery, and Kalman filter, see the Explore Techniques to Estimate Battery State of Charge example.

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View Simulation Results

This plot shows the real and estimated battery state-of-charge.

Results from Real-Time Simulation

This example has been tested on these platforms:

  • Speedgoat™ Performance real-time target machine with an Intel® 3.5 GHz i7 multi-core CPU and 4 GB RAM.

  • dSPACE® SCALEXIO LabBox with Intel® Core XEON E3-1275v3 at 3.5GHz and 4 GB RAM.

You can run this model in real time with a step size of 50 microseconds by using the Simscape local solver. For small sample rates, a task overrun might occur during the initial task execution due to a cold cache. To avoid this overrun, if the selected platform supports these options, relax the start-up behavior by specifying a limited number of task overruns or increasing the sample time of periodic tasks during the start-up phase of the real-time application.

See Also