This paper presents an improved battery parameter estimation method based on typical operating scenarios in hybrid electric vehicles and pure electric vehicles. Compared with the conventional estimation methods, the proposed method takes both the constant-current charging and the dynamic driving scenarios into account, and two separate sets of model parameters are estimated through different parts of the pulse-rest test. The model parameters for the constant-charging scenario are estimated from the data in the pulse-charging periods, while the model parameters for the dynamic driving scenario are estimated from the data in the rest periods, and the length of the fitted dataset is determined by the spectrum analysis of the load current. In addition, the unsaturated phenomenon caused by the long-term resistor-capacitor (RC) network is analyzed, and the initial voltage expressions of the RC networks in the fitting functions are improved to ensure a higher model fidelity. Simulation and experiment results validated the feasibility of the developed estimation method.
This paper proposes an improved interleaved voltage measurement method for battery packs in electric vehicles, which can distinguish between the sensor fault and cell fault without hardware or software redundancy. The coprime constraint in the basic interleaved measurement method is revisited with a new proof, and a graphical interpretation is introduced to visualize the constraint. Based on that, an improved measurement topology is developed to remove the coprime constraint which enables broader application. Moreover, the hardware implementation of the improved method is discussed based on cost and circuit design. The associated improvement in noise performance is mathematically formulated, and the noise limit and trend of the interleaved measurement method are derived. Simulation results match the noise analysis and experiments validate the broader application of the improved method.
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