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首页> 外文会议>IEEE Applied Power Electronics Conference and Exposition >Charge Management for an Inductively Charged On-Demand Battery-Electric Shuttle Service with High Penetration of Renewable Energy
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Charge Management for an Inductively Charged On-Demand Battery-Electric Shuttle Service with High Penetration of Renewable Energy

机译：具有高可再生能源渗透率的感应式按需电池电动穿梭巴士服务的充电管理

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This paper presents a charge management control strategy for an on-demand battery-electric shuttle van operating at the National Renewable Energy Laboratory (NREL) campus and supported by day-time inductive charging at the vehicle’s waiting spot. A new control algorithm has been proposed for reducing the demand charge costs incurred from wireless charging of the on-demand shuttle. A custom controller has been developed to monitor the shuttle, wireless charger, renewable energy generation, and various loads at NREL’s campus, and regulate charging behavior for demand response. The intermittent renewable generation and sporadic operation of the on-demand shuttle service contribute to a high level of uncertainty in expected campus load profile, which must be carefully managed. The control algorithm predicts energy profile to estimate the mobility needs of the vehicle and maintain uninterrupted service during operation while still minimizing peak demand. The proposed controller has been designed and optimized using a Simulink model for the entire system. Next, it has been implemented and tested in real-time on the NREL campus. Two primary vehicle-use cases, charge sustaining and charge depletion operation, are tested under different load profiles and drive cycles to assess the controller’s effectiveness at reducing peak demand and therefore demand charges. The proposed controller showed robust performance under different driving scenarios with high correlation between simulated and experimental data. The results showed that proper demand response can be achieved with an average of 94% reduction of charging loads during peak demand events.
机译：本文提出了一种按需电池电动穿梭货车的充电管理控制策略，该货车在国家可再生能源实验室（NREL）校园中运行，并在车辆的候车点提供日间感应充电。已经提出了一种新的控制算法，以减少因按需穿梭车的无线充电而产生的按需充电成本。已经开发了定制控制器，以监控航天飞机，无线充电器，可再生能源的产生以及NREL校园内的各种负荷，并调节充电行为以响应需求。按需穿梭服务的间歇性可再生能源发电和零星运行会导致预期校园负荷状况的高度不确定性，必须对此加以谨慎管理。控制算法预测能量分布，以估计车辆的机动性需求，并在操作期间保持不间断的服务，同时仍将峰值需求降至最低。拟议的控制器已使用Simulink模型针对整个系统进行了设计和优化。接下来，已在NREL校园中对其进行了实时实施和测试。在不同的负载曲线和行驶周期下测试了两种主要的车辆用例，即电荷维持和电荷消耗操作，以评估控制器在降低峰值需求并因此减少需求电量方面的有效性。所提出的控制器在不同的驾驶场景下表现出鲁棒的性能，并且模拟和实验数据之间具有高度相关性。结果表明，在高峰需求事件期间，平均可减少94％的充电负载，从而可以实现适当的需求响应。

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