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Reliability evaluation of IGBT power module on electric vehicle using big data 被引量:1
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作者 Li Liu Lei Tang +5 位作者 Huaping Jiang Fanyi Wei Zonghua Li changhong du Qianlei Peng Guocheng Lu 《Journal of Semiconductors》 EI CAS CSCD 2024年第5期50-60,共11页
There are challenges to the reliability evaluation for insulated gate bipolar transistors(IGBT)on electric vehicles,such as junction temperature measurement,computational and storage resources.In this paper,a junction... There are challenges to the reliability evaluation for insulated gate bipolar transistors(IGBT)on electric vehicles,such as junction temperature measurement,computational and storage resources.In this paper,a junction temperature estimation approach based on neural network without additional cost is proposed and the lifetime calculation for IGBT using electric vehicle big data is performed.The direct current(DC)voltage,operation current,switching frequency,negative thermal coefficient thermistor(NTC)temperature and IGBT lifetime are inputs.And the junction temperature(T_(j))is output.With the rain flow counting method,the classified irregular temperatures are brought into the life model for the failure cycles.The fatigue accumulation method is then used to calculate the IGBT lifetime.To solve the limited computational and storage resources of electric vehicle controllers,the operation of IGBT lifetime calculation is running on a big data platform.The lifetime is then transmitted wirelessly to electric vehicles as input for neural network.Thus the junction temperature of IGBT under long-term operating conditions can be accurately estimated.A test platform of the motor controller combined with the vehicle big data server is built for the IGBT accelerated aging test.Subsequently,the IGBT lifetime predictions are derived from the junction temperature estimation by the neural network method and the thermal network method.The experiment shows that the lifetime prediction based on a neural network with big data demonstrates a higher accuracy than that of the thermal network,which improves the reliability evaluation of system. 展开更多
关键词 IGBT junction temperature neural network electric vehicles big data
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Aged hematopoietic stem cells entrap regulatory T cells to create a prosurvival microenvironment
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作者 Weinian Liao Chaonan Liu +16 位作者 Ke Yang Jun Chen Yiding Wu Shuzhen Zhang Kuan Yu Lisha Wang Li Ran Mo Chen Fang Chen Yang Xu Song Wang Fengchao Wang Qian Zhang Jinghong Zhao Lilin Ye changhong du Junping Wang 《Cellular & Molecular Immunology》 SCIE CAS CSCD 2023年第10期1216-1231,共16页
Although DNA mutation drives stem cell aging,how mutation-accumulated stem cells obtain clonal advantage during aging remains poorly understood.Here,using a mouse model of irradiation-induced premature aging and middl... Although DNA mutation drives stem cell aging,how mutation-accumulated stem cells obtain clonal advantage during aging remains poorly understood.Here,using a mouse model of irradiation-induced premature aging and middle-aged mice,we show that DNA mutation accumulation in hematopoietic stem cells(HSCs)during aging upregulates their surface expression of major histocompatibility complex class II(MHCII).MHCII upregulation increases the chance for recognition by bone marrow(BM)-resident regulatory T cells(Tregs),resulting in their clonal expansion and accumulation in the HSC niche.On the basis of the establishment of connexin 43(Cx43)-mediated gap junctions,BM Tregs transfer cyclic adenosine monophosphate(cAMP)to aged HSCs to diminish apoptotic priming and promote their survival via activation of protein kinase A(PKA)signaling.Importantly,targeting the HSC–Treg interaction or depleting Tregs effectively prevents the premature/physiological aging of HSCs.These findings show that aged HSCs use an active self-protective mechanism by entrapping local Tregs to construct a prosurvival niche and obtain a clonal advantage. 展开更多
关键词 Hematopoietic stem cell regulatory T cell AGING
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