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Небесная энциклопедия

Космические корабли и станции, автоматические КА и методы их проектирования, бортовые комплексы управления, системы и средства жизнеобеспечения, особенности технологии производства ракетно-космических систем

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Мониторинг СМИ и социальных сетей. Сканирование интернета, новостных сайтов, специализированных контентных площадок на базе мессенджеров. Гибкие настройки фильтров и первоначальных источников.

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Применить Всего найдено 2. Отображено 2.
18-08-2023 дата публикации

Electric drive axle vehicle end and cloud diagnosis method, device and equipment and storage medium

Номер: CN116609081A
Автор: XU LEI, LI JUNHUI, QIN JIAXIN, ZHUANG BING, WU JIANGFEI
Принадлежит:

The invention discloses a vehicle-side and cloud-side diagnosis device and method for an electric drive axle of an electric vehicle, corresponding electronic equipment and a transient computer readable storage medium. The health diagnosis of the electric drive axle is realized by acquiring the data generated in the normal state and the operation process of the electric drive axle, a response scheme is provided, and cloud monitoring and diagnosis are also realized through a communication network. Vehicle-end coping processing is realized through the module arranged at the vehicle end, cloud-end coping processing can also be realized by means of the Internet of Vehicles, artificial intelligence processing and personnel online processing can be realized by relying on cloud-end resources, real-time monitoring and automatic processing are realized, and the health maintenance level of the electric drive axle is greatly improved; according to the scheme, peripheral performance data is introduced ...

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Номер записи: 1
30-05-2023 дата публикации

Battery state estimation method and device and readable storage medium

Номер: CN116184212A
Автор: LI KUN, HUANG FUQIANG, XU JIANCHANG, WANG JINGTAO, KE XICHUN, ZHUANG BING
Принадлежит:

The invention provides a battery state estimation method and device and a readable storage medium. The battery state estimation method comprises the following steps: collecting historical sample data of a plurality of batteries; training the historical sample data at the cloud to obtain model parameters; establishing a local prediction model at the vehicle end according to the model parameters; and collecting feature information parameters of the current battery and inputting the feature information parameters into the local prediction model so as to calculate and obtain the current battery state of the current battery. According to the technical scheme, the accuracy of current battery state estimation can be effectively improved, and the current battery state can be obtained in real time in a network disconnection scene.

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Номер записи: 2