Performance analysis:


Performance analysis:


Performance analysis:


Performance analysis:


**Figure 10.** Robustness to simultaneous changes, SOCini = 1, Qnom = 4.2 Ah (ageing e ffects); (**a**) PFE SOC value versus 3RC ECM battery model true value; (**b**) SOC residual.

**Figure 11.** Robustness to simultaneous changes, SOCini = 0.2, and output temperature profile changes; (**a**) PFE SOC value versus 3RC ECM Li-ion battery model true value for changes only in Rin; (**b**) SOC residual for 20% changes in Rin.

*3.7. MATLAB Simulation Results for Simulink Simscape Battery Model—PFE SOC Estimator Accuracy and Robustness Scenarios*

• Scenario R0. The MATLAB simulation results for this scenario are shown in Appendix A.1, Figure A27a–c, and the statistical criteria values are given in Table 1.

Performance analysis:


Performance analysis:


Performance analysis:


Performance analysis:


Performance analysis:


**Figure 12.** Robustness to simultaneous changes, SOCini = 1, Qnom = 4.2 Ah (ageing effects); (**a**) PFE SOC value versus battery model true value; (**b**) SOC residual.

**Figure 13.** Robustness to simultaneous changes, SOCini = 0.2, and output temperature profile changes; (**a**) PFE SOC value versus battery model true value for changes only in Kp; (**b**) SOC residual for changes only in Kp; (**c**) PFE SOC value versus battery model true value for 10% changes only in Rin; (**d**) SOC residual for changes only in Rin.

Similarly, for the first and second SOC estimators, the MATLAB simulation results of the PFE SOC performance obtained for each model reveal that the PFE SOC estimator works satisfactorily in four scenarios (R0, R1, R2, R3) for the Simscape model, and three scenarios (R0, R1, R3) for the 3RC EMC model. Thus, it is confirmed again that the Simulink model is suitable for use as a support for designing and implementing in a real-time MATLAB environment of SOC estimators in HEV applications.
