Accurate determination of the performance and precise prediction of the state of health (SOH) of lithium-ion batteries are necessary to ensure reliability and efficiency in real-world application. However, most SOH offline studies were based on dynamic stress tests, which only reflect the universal rule of degradation, but are not necessarily applicable for real-world applications. This paper presents an experimental evaluation of two different operations of real-world plug-in hybrid electric vehicles with LiFePO₄ batteries as energy-storage systems. First, the LiFePO₄ batteries were subjected to a set of comparative experimental tests that consider the effects of charge depleting (CD) and charge sustaining (CS) operations. Then, different voltage analysis along with the close-to-equilibrium open circle voltage was utilized to evaluate the performance of the batteries in life cycles. Finally, a qualitative relationship between the external factors (the percentage of time of CD/CS operations during the entire driving range) and the degradation mechanism was built with the help of the proposed methods. Results indicated that the external factors affect the degree of the batteries degradation, but not up to the point when the capacity fading stage occurs. This relationship contributes to the foundation for plug-in hybrid electric vehicles’ (PHEVs’) energy management strategy or battery management system control strategy.

Accurate battery modeling is essential for the state-of-charge (SOC) estimation of electric vehicles, especially when vehicles are operated in dynamic processes. Temperature is a significant factor for battery characteristics, especially for the hysteresis phenomenon. Lack of existing literatures on the consideration of temperature influence in hysteresis voltage can result in errors in SOC estimation. Therefore, this study gives an insight to the equivalent circuit modeling, considering the hysteresis and temperature effects. A modified one-state hysteresis equivalent circuit model was proposed for battery modeling. The characterization of hysteresis voltage versus SOC at various temperatures was acquired by experimental tests to form a static look-up table. In addition, a strong tracking filter (STF) was applied for SOC estimation. Numerical simulations and experimental tests were performed in commercial 18650 type Li(Ni_1/3Co_1/3Mn_1/3)O₂ battery. The results were systematically compared with extended Kalman filter (EKF) and unscented Kalman filter (UKF). The results of comparison showed the following: (1) the modified model has more voltage tracking capability than the original model; and (2) the modified model with STF algorithm has better accuracy, robustness against initial SOC error, voltage measurement drift, and convergence behavior than EKF and UKF.