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A Generalized Approach for Adaptive Energy Management of Electric and Hybrid Electric Vehicles

机译:电动电动汽车自适应能源管理的广义方法

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An adaptive algorithm based on weighted recursive least squares is derived and implemented. The generality of the approach is underscored by the application of the algorithm to hybrid-electric-vehicle lead acid and electric-vehicle nickel metal hydride (NiMH) battery systems. The algorithm is fully recursive in that the only variables required for on-line regression are those of the previous time step and the current time step. The output from the adaptive algorithm is the battery state of charge (remaining energy), state of health (relative to the battery's nominal rating), and power capability. Such algorithms are likely to play a critical role in optimal operation of HEV's and onboard-diagnostics. The behavior of the algorithm in terms of convergence, accuracy, and robustness is examined.
机译:派生和实现了一种基于加权递归最小二乘的自适应算法。通过将算法应用于混合动力 - 电动 - 载体铅酸和电动 - 电动镍金属氢化物(NiMH)电池系统,强调了该方法的一般性。该算法完全递归,因为在线回归所需的唯一变量是前一时间步长和当前时间步长的变量。自适应算法的输出是电池充电状态(剩余能量),健康状态(相对于电池的标称额定值)和功率能力。此类算法可能在HEV和车载诊断的最佳操作中发挥关键作用。检查算法在收敛,准确性和鲁棒性方面的行为。

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