Výsledky vyhledávání - "Jiang, Weiran"

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Integrated Power and Thermal Management for Enhancing Energy Efficiency and Battery Life in Connected and Automated Electric Vehicles

Autor: Li, Dongjun, Hu, Qiuhao, Jiang, Weiran, Dong, Haoxuan, Song, Ziyou

Effective power and thermal management are essential for ensuring battery efficiency, safety, and longevity in Connected and Automated Electric Vehicles (CAEVs). However, real-time implementation is challenging due to the multi-timescale dynamics and

Externí odkaz: http://arxiv.org/abs/2411.05298

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Bias-Compensated State of Charge and State of Health Joint Estimation for Lithium Iron Phosphate Batteries

Autor: Yi, Baozhao, Du, Xinhao, Zhang, Jiawei, Wu, Xiaogang, Hu, Qiuhao, Jiang, Weiran, Hu, Xiaosong, Song, Ziyou

Accurate estimation of the state of charge (SOC) and state of health (SOH) is crucial for the safe and reliable operation of batteries. Voltage measurement bias highly affects state estimation accuracy, especially in Lithium Iron Phosphate (LFP) batt

Externí odkaz: http://arxiv.org/abs/2401.08136

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Deep Joint Source Channel Coding With Attention Modules Over MIMO Channels

Autor: Jiang, Weiran, Chen, Wei, Ai, Bo

In this paper, we propose two deep joint source and channel coding (DJSCC) structures with attention modules for the multi-input multi-output (MIMO) channel, including a serial structure and a parallel structure. With singular value decomposition (SV

Externí odkaz: http://arxiv.org/abs/2311.07041

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Driving behavior-guided battery health monitoring for electric vehicles using machine learning

Autor: Jiang, Nanhua, Zhang, Jiawei, Jiang, Weiran, Ren, Yao, Lin, Jing, Khoo, Edwin, Song, Ziyou

Publikováno v: Applied Energy (2024)

An accurate estimation of the state of health (SOH) of batteries is critical to ensuring the safe and reliable operation of electric vehicles (EVs). Feature-based machine learning methods have exhibited enormous potential for rapidly and precisely mo

Externí odkaz: http://arxiv.org/abs/2309.14125

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