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Assessment of Minimum Fuel Consumption Operation Strategy for Hybrid Powersport Drive-Trains by Means of Dynamic Programming Method

机译:通过动态规划方法评估混合动力驱动训练的最小燃料消耗运算策略

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The hybrid-electric drivetrain permits a multitude of new control strategies like brake energy recuperation, engine start-stop operation, shifting of engine working point, as well as in some situations pure electric driving. Overall this typically allows a reduction of fuel consumption and therefore of carbon dioxide emissions. During the development process of the vehicle various drivetrain configurations have to be considered and compared. This includes decisions regarding the topology - like the position of the electrical machine in the drivetrain (e.g. at the gearbox input or output shaft), as well as the selection of the needed components based on their parameters (nominal power, energy content of the battery, efficiency etc.). To compare the chosen variants, typically the calculated fuel consumption for a given driving cycle is used. For this simulation an energy management strategy is needed, which defines the power distribution between ICE, electric machine and mechanical brakes. However, the used operation strategy has a large influence on the achieved fuel consumption. Typically used online strategies (rule based approaches, neural networks, … ) have to be adapted for each configuration individually. Nevertheless, it cannot be guaranteed, that the individually optimized controllers work equally well for each configuration. To circumvent this problem, we use a mathematical method (so called dynamic programming) to calculate an optimal energy management for each considered configuration. This optimum represents a set of operation modes and operation points, which lead to the absolute minimum fuel consumption. Thereby a comparison of different configurations without influence of the control strategy becomes possible.
机译:混合动力传动系统允许众多的新控制策略,如制动能量恢复,发动机启动操作,发动机工作点的移位,以及一些情况纯电动驱动。总的来说,这通常允许减少燃料消耗并因此减少二氧化碳排放。在车辆的开发过程中,必须考虑和比较各种动力传动系统配置。这包括关于拓扑结构的决定 - 就像动机中的电机在动机中的位置(例如在齿轮箱输入或输出轴上),以及基于它们的参数选择所需的组件(标称电源,电池的能量含量,效率等)。为了比较所选择的变型,通常使用所计算的给定驾驶循环的燃料消耗。对于此模拟,需要一种能源管理策略,其定义了冰,电机和机械制动器之间的功率分配。然而,使用的操作策略对实现的燃料消耗具有很大影响。通常使用在线策略(基于规则的方法,神经网络,...)必须单独适用于每个配置。尽管如此,它无法保证,单独优化的控制器对于每个配置同样适用。为了避免这个问题,我们使用数学方法(所谓的动态编程)来计算每个考虑的配置的最佳能量管理。该最佳表示一组操作模式和操作点,这导致绝对的最小燃料消耗。由此可以比较不同配置而不影响控制策略。

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