arrow
返回
胡

胡晓松 (Hu, Xiaosong)

Chongqing University

0H指数
113论文数
0被引数
收录论文 110
发表时间
Data efficient health prognostic for batteries based on sequential information-driven probabilistic neural network基于序贯信息驱动概率神经网络的电池数据高效健康预测
err2022-10-01
err54
errOAAI
errChe, Yunhong; Zheng, Yusheng; Wu, Yue; Sui, Xin; Bharadwaj, Pallavi; Stroe, Daniel-Ioan; Yang, Yalian; Hu, Xiaosong; Teodorescu, Remus
err分享
err收藏
A Platoon Control Method Based on DMPC for Connected Energy-Saving Electric Vehicles
err2022-09-01
err20
PREAI
errPi, Dawei; Xue, Pengyu; Xie, Boyuan; Wang, Hongliang; Tang, Xiaolin; Hu, Xiaosong
err分享
err收藏
err分享
err收藏
Q-Learning-Based Supervisory Control Adaptability Investigation for Hybrid Electric Vehicles
err2022-07-01
err42
PREAI
errXu, Bin; Tang, Xiaolin; Hu, Xiaosong; Lin, Xianke; Li, Huayi; Rathod, Dhruvang; Wang, Zhe
err分享
err收藏
A Review of Second-Life Lithium-Ion Batteries for Stationary Energy Storage Applications用于固定储能应用的二次锂离子电池综述
err2022-06-01
err61
PREAI
errHu, Xiaosong; Deng, Xinchen; Wang, Feng; Deng, Zhongwei; Lin, Xianke; Teodorescu, Remus; Pecht, Michael G.
err分享
err收藏
Battery health evaluation using a short random segment of constant current charging
err2022-05-01
err30
errOAAI
errDeng, Zhongwei; Hu, Xiaosong; Xie, Yi; Xu, Le; Li, Penghua; Lin, Xianke; Bian, Xiaolei
err分享
err收藏
Increasing energy utilization of battery energy storage via active multivariable fusion-driven balancing
errENERGY
IF9.4
err2022-03-01
err10
PREAI
errLi, Penghua; Liu, Jianfei; Deng, Zhongwei; Yang, Yalian; Lin, Xianke; Couture, Jonathan; Hu, Xiaosong
err分享
err收藏
err分享
err收藏
Multi-Objective Design Optimization of a Novel Dual-Mode Power-Split Hybrid Powertrain
err2022-01-01
err24
PREAI
errTang, Xiaolin; Zhang, Jieming; Cui, Xiangyang; Lin, Xianke; Grzesiak, Lech M.; Hu, Xiaosong
err分享
err收藏
The role and application of convex modeling and optimization in electrified vehicles
err2022-01-01
err24
PREAI
errLi, Yapeng; Tang, Xiaolin; Lin, Xianke; Grzesiak, Lech; Hu, Xiaosong
err分享
err收藏
State of health prognostics for series battery packs: A universal deep learning method串联电池组的健康状态预测: 一种通用的深度学习方法
errENERGY
IF9.4
err2022-01-01
err67
PREAI
errChe, Yunhong; Deng, Zhongwei; Li, Penghua; Tang, Xiaolin; Khosravinia, Kavian; Lin, Xianke; Hu, Xiaosong
err分享
err收藏

研究方向

重庆大学车辆动力系统团队研究工作总介绍视频 一车辆新型储能系统电化学单体耦合模型状态估计电池组热管理低温预热整车热管理电池组模型电池组均衡管理电池组故障诊断寿命预测自动化拆解技术经济性分析车辆电气化推进系统混合动力系统物理层设计混合动力汽车构型分析混合动力系统部件配置优化模型预测能量管理 MPC强化学习能量管理 RL传动控制 三智能网联化控制V2V/V2I网联节能型汽车信息物理控制动态交通反馈数据支持的能量管理PV和智能家居能量管理智能家居电池配置优化PEVPV和BESS集成优化