The health management of batteries is a key enabler for the adoption of Electric Vertical Take-off and Landingvehicles (eVTOLs). Currently, few studies consider the health management of eVTOL batteries. One distinctch...The health management of batteries is a key enabler for the adoption of Electric Vertical Take-off and Landingvehicles (eVTOLs). Currently, few studies consider the health management of eVTOL batteries. One distinctcharacteristic of batteries for eVTOLs is that the discharge rates are significantly larger during take-off andlanding, compared with the battery discharge rates needed for automotives. Such discharge protocols areexpected to impact the long-run health of batteries. This paper proposes a data-driven machine learningframework to estimate the state-of-health and remaining-useful-lifetime of eVTOL batteries under varying flightconditions and taking into account the entire flight profile of the eVTOLs. Three main features are consideredfor the assessment of the health of the batteries: charge, discharge and temperature. The importance of thesefeatures is also quantified. Considering battery charging before flight, a selection of missions for state-ofhealth and remaining-useful-lifetime prediction is performed. The results show that indeed, discharge-relatedfeatures have the highest importance when predicting battery state-of-health and remaining-useful-lifetime.Using several machine learning algorithms, it is shown that the battery state-of-health and remaining-useful-lifeare well estimated using Random Forest regression and Extreme Gradient Boosting, respectively.展开更多
根据旋翼机和固定翼飞机的气动理论开发了一个综合方法过程用于估算电动垂直起降(Electric vertical takeoff and landing, e VTOL)飞行器的飞行性能。这种飞机通常采用多旋翼垂直飞行,螺旋桨和机翼的不同组合方式实现飞行。其中,对旋...根据旋翼机和固定翼飞机的气动理论开发了一个综合方法过程用于估算电动垂直起降(Electric vertical takeoff and landing, e VTOL)飞行器的飞行性能。这种飞机通常采用多旋翼垂直飞行,螺旋桨和机翼的不同组合方式实现飞行。其中,对旋翼和螺旋桨的气动性能采用传统动量理论分析和旋翼元素分析。本文利用此综合理论研究了12架e VTOL飞行器的飞行性能,包括多旋翼飞行器、矢量推进飞行器和升力巡航飞行器。计算了悬停、爬升和下降以及巡航水平飞行,不同飞行状态时驱动电机、旋翼和机身的飞行特性。据此,可以进一步确定电力推进系统的性能指标,以匹配螺旋桨或旋翼,从而满足飞行任务。展开更多
为迎接电动垂直起降航空器的到来,降低平均无故障时间,对电动垂直起降(electric vertical takeoff and landing,eVTOL)航空器的一般运行场景和系统构成做出了分析,并从人为因素、设备因素、环境因素和其他因素中提取了可能的失效诱因;...为迎接电动垂直起降航空器的到来,降低平均无故障时间,对电动垂直起降(electric vertical takeoff and landing,eVTOL)航空器的一般运行场景和系统构成做出了分析,并从人为因素、设备因素、环境因素和其他因素中提取了可能的失效诱因;构建了失控坠地和空中碰撞的贝叶斯网络,并依据所建网络和通过不同专家得到的概率值计算控制失效情况下失控坠地和中间事件发生概率,然后进行反向推断,推演事故发生主要诱因。结果表明:电动垂直起降航空器正常运行发生事故的概率为9.648×10^(-7),其中,控制失效、飞控系统断电/故障是事故主要诱因,计算结果可为电动垂直起降航空器安全运行防控提供依据。展开更多
文摘The health management of batteries is a key enabler for the adoption of Electric Vertical Take-off and Landingvehicles (eVTOLs). Currently, few studies consider the health management of eVTOL batteries. One distinctcharacteristic of batteries for eVTOLs is that the discharge rates are significantly larger during take-off andlanding, compared with the battery discharge rates needed for automotives. Such discharge protocols areexpected to impact the long-run health of batteries. This paper proposes a data-driven machine learningframework to estimate the state-of-health and remaining-useful-lifetime of eVTOL batteries under varying flightconditions and taking into account the entire flight profile of the eVTOLs. Three main features are consideredfor the assessment of the health of the batteries: charge, discharge and temperature. The importance of thesefeatures is also quantified. Considering battery charging before flight, a selection of missions for state-ofhealth and remaining-useful-lifetime prediction is performed. The results show that indeed, discharge-relatedfeatures have the highest importance when predicting battery state-of-health and remaining-useful-lifetime.Using several machine learning algorithms, it is shown that the battery state-of-health and remaining-useful-lifeare well estimated using Random Forest regression and Extreme Gradient Boosting, respectively.
文摘根据旋翼机和固定翼飞机的气动理论开发了一个综合方法过程用于估算电动垂直起降(Electric vertical takeoff and landing, e VTOL)飞行器的飞行性能。这种飞机通常采用多旋翼垂直飞行,螺旋桨和机翼的不同组合方式实现飞行。其中,对旋翼和螺旋桨的气动性能采用传统动量理论分析和旋翼元素分析。本文利用此综合理论研究了12架e VTOL飞行器的飞行性能,包括多旋翼飞行器、矢量推进飞行器和升力巡航飞行器。计算了悬停、爬升和下降以及巡航水平飞行,不同飞行状态时驱动电机、旋翼和机身的飞行特性。据此,可以进一步确定电力推进系统的性能指标,以匹配螺旋桨或旋翼,从而满足飞行任务。
文摘为迎接电动垂直起降航空器的到来,降低平均无故障时间,对电动垂直起降(electric vertical takeoff and landing,eVTOL)航空器的一般运行场景和系统构成做出了分析,并从人为因素、设备因素、环境因素和其他因素中提取了可能的失效诱因;构建了失控坠地和空中碰撞的贝叶斯网络,并依据所建网络和通过不同专家得到的概率值计算控制失效情况下失控坠地和中间事件发生概率,然后进行反向推断,推演事故发生主要诱因。结果表明:电动垂直起降航空器正常运行发生事故的概率为9.648×10^(-7),其中,控制失效、飞控系统断电/故障是事故主要诱因,计算结果可为电动垂直起降航空器安全运行防控提供依据。
