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In an authors' previous SAE publication, an energy management control strategy has been proposed for the basic, charge-depleting/charge-sustaining (CD/CS) regime of an Extended Range Electric Vehicle (EREV). The strategy is based on combining a rule-based controller, including a state-of-charge regulator, with an equivalent consumption minimization strategy. This paper presents an extension of the control strategy, which can provide a favorable vehicle behavior in the more general blended (BLND) operating regime, as well. Dynamic programming-based control variables optimization is first conducted to gain an insight into the vehicle optimal behavior in the BLND regime, facilitate the feedback control strategy development/extension, and serve as a benchmark for the control strategy verification. Next, a parameter optimization method is applied to find optimal values of critical engine on/off thresholds.

A dynamic programming-based algorithm is developed and used for off-line optimization of range extended electric vehicle power train control variables over standardized certification driving cycles. The aim is to minimize the fuel consumption subject to battery state-of-charge constraints and physical limits of different power train variables. The control variables to be optimized include engine torque and electric machine speed, as well as a variable that selects the power train operating mode. The optimization results are presented for four characteristic certification driving cycles and characteristic vehicle operating regimes including electric driving during charge depleting mode, hybrid driving during charge sustaining mode, and combined/blended regime.

The bond graph method is used to model kinematics of various one-mode and two-mode series-parallel configurations of hybrid electric vehicle transmissions. Based on the derived speed and torque equations, a comparative analysis of hybrid transmissions steady-state behaviors is conducted. An example of control-oriented bond graph modeling of hybrid transmission dynamics is presented, as well.