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Hybrid model predictive power flow control of a fuel cell-battery vehicle

机译:燃料电池汽车的混合模型预测功率流控制

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This paper considers optimal power flow control of a fuel cell-battery hybrid vehicle (FCHV) powertrain having three distinct modal configurations (modes): electric motor propelling/battery discharging, propelling/charging, and generating/charging. Each mode has a distinct set of dynamics and constraints. Using component dynamical/algebraic models appropriate to power management, the paper develops a supervisory-level switched system model as an interconnection of subsystems. Given the model, the paper sets forth a hybrid model predictive control strategy based on a minimization of a performance index (PI) that trades off tracking and fuel economy in each operational mode. Specifically the PI trades off velocity tracking error, battery state of charge variance, and hydrogen usage while penalizing frictional braking. The optimization is performed using an embedded system model and collocation with MATLAB's fmincon to compute mode switches and continuous time controls thereby avoiding the computational complexity of alternate approaches based on, e.g., mixed integer programming. To demonstrate the approach, an example FCHV following trapezoidal and sawtooth drive profiles is simulated. PI weights are varied for reduced hydrogen use and higher final battery charge to illustrate various performance trade-offs.
机译:本文考虑了具有三种不同模态配置(模式)的燃料电池电池混合动力车辆(FCHV)动力系的最佳功率流量控制:电动机推进/电池放电,推进/充电和产生/充电。每个模式都有一个不同的动态和约束。使用适合电源管理的组件动态/代数模型,该纸张开发了一个监控级交换系统模型作为子系统的互连。鉴于该模型,本文阐述了一种混合模型预测控制策略,基于在每种操作模式下交易跟踪和燃料经济性的性能指数(PI)的最小化。具体而言,PI交易速度跟踪误差,电池电量方差和氢气用途,同时惩罚摩擦制动。使用嵌入式系统模型和与Matlab的Fmincon搭配来执行优化以计算模式开关和连续时间控制,从而避免了基于例如混合整数编程的替代方法的计算复杂性。为了证明该方法,模拟了梯形和锯齿驱动器轮廓之后的示例FCHV。降低氢气使用和更高的最终电池充电的PI重量变化,以说明各种性能权衡。

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