Partnership for a new generation of vehicles (PNGV) model is a conventional battery equivalent circuit model (ECM). However, identifying the best parameters for this model is a challenge. In this study, the PNGV model is transformed into a directly identifiable difference equation to identify its parameters. Subsequently, the model reference adaptive system (MRAS) is used to realize the real‐time identification of the model parameters. The identification accuracy of the MRAS is found to be superior to that of the recursive extended least square algorithm. For a single hybrid pulse power characterization (HPPC), the PNGV model identified by the MRAS can achieve a high‐precision terminal voltage estimation. For lithium iron phosphate, lithium titanate, and nickel‐metal hydride batteries, the root mean square errors are 0.024, 0.048, and 0.020 V, respectively. Besides, the real‐time state of charge (SOC) estimation can be realized by the identified open‐circuit voltage (OCV). The average errors of the three batteries are only −0.02, −0.01, and −0.01, respectively. Since the PNGV model has a capacity of describing the change of OCV with the current accumulation effect, the model is only suitable for simulating single HPPC or positive‐negative pulses with equal amplitude and not for other current pulses. This is a major drawback of the PNGV model. The real‐time PNGV model parameters identification method proposed in this study can provide a solid foundation for various state estimation of a battery.
Novelty Statement
- Transformation of the PNGV model into a difference equation that can be directly identified.
- Real‐time identification of the PNGV model parameters via the MRAS.
- The identified OCV realized the real‐time SOC estimation and discussed the deficiencies of the PNGV model.