Y. Zhang, Zhichao Fu, Qihong Chen, Liyan Zhang, Keliang Zhou, Zhihua Deng
{"title":"质子交换膜燃料电池数据驱动的自抗扰净功率控制*","authors":"Y. Zhang, Zhichao Fu, Qihong Chen, Liyan Zhang, Keliang Zhou, Zhihua Deng","doi":"10.1109/CVCI51460.2020.9338567","DOIUrl":null,"url":null,"abstract":"Proton exchange membrane fuel cell (PEMFC) is an environmentally friendly and efficient power generation device. It offers promising advantages over conventional power sources in backup power supplies, distributed generation and vehicle power. A rapid response to the actual power required by load is of great significance to improve the economy and efficiency of the system. However, due to various uncertainties such as frequent disturbances and inaccurate model, the net power control has certain challenges. Therefore, a data-driven nonlinear subspace identification method is developed to build the model of net power. A segmented and consecutive step response of net power for PEMFC system are identified and analyzed, the models are verified by high-fidelity simulation data. Data-driven active disturbance rejection control (ADRC) algorithm is developed to control the model. Internal and external disturbances are considered as a total term, which is estimated and compensated by real-time input-output data and ADRC, respectively. Compared with the integral absolute error of the conventional proportion integral and proportion integral derivative control, the performance of ADRC is improved by about 89.81 % and 78.92%, respectively. Therefore, the proposed ADRC can improve the dynamic performance of PEMFC system in terms of set-point tracking performance, disturbance rejection performance and robustness.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data-driven active disturbance rejection net power control of proton exchange membrane fuel cell*\",\"authors\":\"Y. Zhang, Zhichao Fu, Qihong Chen, Liyan Zhang, Keliang Zhou, Zhihua Deng\",\"doi\":\"10.1109/CVCI51460.2020.9338567\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Proton exchange membrane fuel cell (PEMFC) is an environmentally friendly and efficient power generation device. It offers promising advantages over conventional power sources in backup power supplies, distributed generation and vehicle power. A rapid response to the actual power required by load is of great significance to improve the economy and efficiency of the system. However, due to various uncertainties such as frequent disturbances and inaccurate model, the net power control has certain challenges. Therefore, a data-driven nonlinear subspace identification method is developed to build the model of net power. A segmented and consecutive step response of net power for PEMFC system are identified and analyzed, the models are verified by high-fidelity simulation data. Data-driven active disturbance rejection control (ADRC) algorithm is developed to control the model. Internal and external disturbances are considered as a total term, which is estimated and compensated by real-time input-output data and ADRC, respectively. Compared with the integral absolute error of the conventional proportion integral and proportion integral derivative control, the performance of ADRC is improved by about 89.81 % and 78.92%, respectively. Therefore, the proposed ADRC can improve the dynamic performance of PEMFC system in terms of set-point tracking performance, disturbance rejection performance and robustness.\",\"PeriodicalId\":119721,\"journal\":{\"name\":\"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVCI51460.2020.9338567\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVCI51460.2020.9338567","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data-driven active disturbance rejection net power control of proton exchange membrane fuel cell*
Proton exchange membrane fuel cell (PEMFC) is an environmentally friendly and efficient power generation device. It offers promising advantages over conventional power sources in backup power supplies, distributed generation and vehicle power. A rapid response to the actual power required by load is of great significance to improve the economy and efficiency of the system. However, due to various uncertainties such as frequent disturbances and inaccurate model, the net power control has certain challenges. Therefore, a data-driven nonlinear subspace identification method is developed to build the model of net power. A segmented and consecutive step response of net power for PEMFC system are identified and analyzed, the models are verified by high-fidelity simulation data. Data-driven active disturbance rejection control (ADRC) algorithm is developed to control the model. Internal and external disturbances are considered as a total term, which is estimated and compensated by real-time input-output data and ADRC, respectively. Compared with the integral absolute error of the conventional proportion integral and proportion integral derivative control, the performance of ADRC is improved by about 89.81 % and 78.92%, respectively. Therefore, the proposed ADRC can improve the dynamic performance of PEMFC system in terms of set-point tracking performance, disturbance rejection performance and robustness.