A model-based Li-ion battery control strategy using estimated CSC (Critical Surface Charge) is proposed to prevent excessive battery charging and discharging in a series HEV (Hybrid Electric Vehicle). The series-HEV simulation framework includes a finely discretised electrode-averaged Li-ion battery model to capture realistic battery voltage drops with respect to applied current. The base supervisory controller has four different operating modes, and the modes are changed based on driving conditions. The thermostatic SOC control strategy is used to distribute the power between the engine and the battery. The controller is augmented by the proposed battery management strategy that modifies the allowable battery power limits using the estimated Li-ion concentration at the electrode solid surface (CSC). The final controller adjusts the allowable power limits in real time during highly dynamic charging or discharging events, thus ensuring safe and robust battery operation during aggressive driving conditions. Instances of over-charging or over-discharging are successfully prevented. This enables the reduction of battery size and cost without any significant loss of performance or reliability. The controller development is summarised as follows: the CSC used in the control design is estimated by the electrochemical model-driven EKF (Extended Kalman Filter). The estimated CSC is then manipulated using the FIR (Finite Impulse Response) filter to remove fast transient fluctuations and to track long-term trends. The allowable battery power limit is modified through feedback of the filtered CSC from the bulk Li-ion concentration. The feedback gain is determined to constrain the resulting terminal voltage within the battery operation limits (2.7 ∼ 3.9 volt).
Battery power management in heavy-duty HEVs based on the estimated critical surface charge
International Journal of Vehicle Design ; 61 , 1-4 ; 108-127
2013
20 Seiten, 13 Bilder, 1 Tabelle, 23 Quellen
Aufsatz (Zeitschrift)
Englisch
Battery power management in heavy–duty HEVs based on the estimated critical surface charge
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