Tobias Schürmann, Nils Kutter, S. Schwab, S. Hohmann
{"title":"利用柔性负载缓解汽车电网的功率峰值","authors":"Tobias Schürmann, Nils Kutter, S. Schwab, S. Hohmann","doi":"10.1109/ICAT54566.2022.9811195","DOIUrl":null,"url":null,"abstract":"In the recent decades, the complexity of the auto-motive power network (APN) has been steadily increasing. This growing complexity is due to the electrification of former mechanical components and the increasing integration of telecommunication and entertainment devices. Additionally, autonomous driving functionalities lead to safety requirements that have to be met by the power supply infrastructure. Another challenge is the deviation in update cycles of the vehicle platform and the entertainment and telecommunication components. Thus, a modular and flexible power network management which allows for plug-and-play integration of new components is needed. In a previous contribution, we presented an auction-based approach for a modular load management in modern vehicles with multiple voltage levels. In this paper, we extend this basic approach by predictive measures in order to exploit flexible load capabilities by load shifting or load shaping. This leads to mitigated power peaks in the APN. As a result, the strain on the battery storage can be reduced and the forced deactivation of comfort components can be prevented. We demonstrate the working principle in a simulative study and show the effectiveness of the combination between the basic auction-based load management and the predictive extension introduced in this paper.","PeriodicalId":414786,"journal":{"name":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","volume":"358 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Mitigating Power Peaks in Automotive Power Networks by Exploitation of Flexible Loads\",\"authors\":\"Tobias Schürmann, Nils Kutter, S. Schwab, S. Hohmann\",\"doi\":\"10.1109/ICAT54566.2022.9811195\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the recent decades, the complexity of the auto-motive power network (APN) has been steadily increasing. This growing complexity is due to the electrification of former mechanical components and the increasing integration of telecommunication and entertainment devices. Additionally, autonomous driving functionalities lead to safety requirements that have to be met by the power supply infrastructure. Another challenge is the deviation in update cycles of the vehicle platform and the entertainment and telecommunication components. Thus, a modular and flexible power network management which allows for plug-and-play integration of new components is needed. In a previous contribution, we presented an auction-based approach for a modular load management in modern vehicles with multiple voltage levels. In this paper, we extend this basic approach by predictive measures in order to exploit flexible load capabilities by load shifting or load shaping. This leads to mitigated power peaks in the APN. As a result, the strain on the battery storage can be reduced and the forced deactivation of comfort components can be prevented. We demonstrate the working principle in a simulative study and show the effectiveness of the combination between the basic auction-based load management and the predictive extension introduced in this paper.\",\"PeriodicalId\":414786,\"journal\":{\"name\":\"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)\",\"volume\":\"358 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAT54566.2022.9811195\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 XXVIII International Conference on Information, Communication and Automation Technologies (ICAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAT54566.2022.9811195","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mitigating Power Peaks in Automotive Power Networks by Exploitation of Flexible Loads
In the recent decades, the complexity of the auto-motive power network (APN) has been steadily increasing. This growing complexity is due to the electrification of former mechanical components and the increasing integration of telecommunication and entertainment devices. Additionally, autonomous driving functionalities lead to safety requirements that have to be met by the power supply infrastructure. Another challenge is the deviation in update cycles of the vehicle platform and the entertainment and telecommunication components. Thus, a modular and flexible power network management which allows for plug-and-play integration of new components is needed. In a previous contribution, we presented an auction-based approach for a modular load management in modern vehicles with multiple voltage levels. In this paper, we extend this basic approach by predictive measures in order to exploit flexible load capabilities by load shifting or load shaping. This leads to mitigated power peaks in the APN. As a result, the strain on the battery storage can be reduced and the forced deactivation of comfort components can be prevented. We demonstrate the working principle in a simulative study and show the effectiveness of the combination between the basic auction-based load management and the predictive extension introduced in this paper.