Battery State-of-Health Estimation
This example shows how to estimate the battery internal resistance and state-of-health (SOH) by using an adaptive Kalman filter. The initial state-of-charge (SOC) of the battery is equal to 0.6. The estimator uses an initial condition for the SOC equal to 0.65. The battery keeps charging and discharging for 10 hours. The unscented Kalman filter estimator converges to the real value of the SOC while also estimating the internal resistance. To use a different Kalman filter implementation, in the SOC Estimator (Kalman Filter) block, set the Filter type parameter to the desired value.
The plot below shows the real and estimated battery state-of-charge, estimated terminal resistance, and estimated state-of-health of the battery.
Results from Real-Time Simulation
This example has been tested on a Speedgoat Performance real-time target machine with an Intel® 3.5 GHz i7 multi-core CPU. This model can run in real time with a step size of 100 microseconds.