Modeling and Control of a Hybrid-Electric Vehicle for Drivability and Fuel Economy Improvements
Modeling and Control of a Hybrid-Electric Vehicle for Drivability and Fuel Economy Improvements
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发表时间：
2008
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通讯作者：
K. Koprubasi
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作者：
K. Koprubasi
在过去几十年中，石油储量的逐渐减少和对能源需求的不断增加导致汽车制造商寻求替代解决方案，以减少对化石燃料的依赖。一种可行的技术，能够显着提高整体坦克到车轮的车辆能量转换效率是电动和传统驱动系统的混合。复杂的混合动力总成配置需要仔细协调执行器和车载能源，以最佳利用节能效益。最优性这个术语通常与燃油经济性有关，尽管其他指标如驾驶性能和废气排放也同样重要。本论文主要研究混合动力电动汽车（HEV）控制策略的设计，旨在最大限度地减少燃料消耗，同时保持良好的车辆驾驶性能。为了便于控制器的数学模型的HEV系统的基础上的设计，一个动态模型，能够预测纵向车辆的响应在低到中频区域（高达10 Hz）的并联HEV配置开发。该模型进行了验证，从各种驱动模式，包括纯电动，纯发动机和混合动力的实验数据。该模型的高保真度使其能够准确识别关键的驾驶性能问题，如时间滞后，分流，洗牌，扭矩孔和犹豫。使用来自车辆模型的信息，能源管理策略的开发和实施的测试车辆。所得到的控制策略具有混合结构，在这个意义上，主要操作模式（混合模式）
The gradual decline of oil reserves and the increasing demand for energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall tank-to-wheel vehicle energy conversion efficiencies is the hybridization of electrical and conventional drive systems. Sophisticated hybrid powertrain configurations require careful coordination of the actuators and the onboard energy sources for optimum use of the energy saving benefits. The term optimality is often associated with fuel economy, although other measures such as drivability and exhaust emissions are also equally important. This dissertation focuses on the design of hybrid-electric vehicle (HEV) control strategies that aim to minimize fuel consumption while maintaining good vehicle drivability. In order to facilitate the design of controllers based on mathematical models of the HEV system, a dynamic model that is capable of predicting longitudinal vehicle responses in the low-to-mid frequency region (up to 10 Hz) is developed for a parallel HEV configuration. The model is validated using experimental data from various driving modes including electric only, engine only and hybrid. The high fidelity of the model makes it possible to accurately identify critical drivability issues such as time lags, shunt, shuffle, torque holes and hesitation. Using the information derived from the vehicle model, an energy management strategy is developed and implemented on a test vehicle. The resulting control strategy has a hybrid structure in the sense that the main mode of operation (the hybrid