混合动力和电动动力系统测试的电池阻抗仿真

O. Konig, S. Jakubek, G. Prochart
{"title":"混合动力和电动动力系统测试的电池阻抗仿真","authors":"O. Konig, S. Jakubek, G. Prochart","doi":"10.1109/VPPC.2012.6422636","DOIUrl":null,"url":null,"abstract":"With battery emulators, development engineers can test electrical drives on testbeds without the need for costly battery prototypes. Furthermore, valuable time for battery pre-conditioning can be saved. However, high quality battery emulation is a challenge that requires a good battery model and accurate emulation of the model with a controllable power supply. A high-fidelity nonlinear battery model based on local model networks is used. This allows the extraction of local linear models for impedance emulation with a switch model DC-DC converter. Local linear battery models and a model of the converter are combined to a prediction model which is used for designing a model predictive controller. In contrast to existing impedance emulation schemes with cascaded feedback loops, the virtual impedance is included in the inner voltage control loop in order to achieve the highest possible bandwidth. Owing to constrained optimal control, this is achieved while respecting control variable constraints and inductor current safety limits. Experimental results show the effectiveness of the proposed battery impedance emulation scheme.","PeriodicalId":341659,"journal":{"name":"2012 IEEE Vehicle Power and Propulsion Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Battery impedance emulation for hybrid and electric powertrain testing\",\"authors\":\"O. Konig, S. Jakubek, G. Prochart\",\"doi\":\"10.1109/VPPC.2012.6422636\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With battery emulators, development engineers can test electrical drives on testbeds without the need for costly battery prototypes. Furthermore, valuable time for battery pre-conditioning can be saved. However, high quality battery emulation is a challenge that requires a good battery model and accurate emulation of the model with a controllable power supply. A high-fidelity nonlinear battery model based on local model networks is used. This allows the extraction of local linear models for impedance emulation with a switch model DC-DC converter. Local linear battery models and a model of the converter are combined to a prediction model which is used for designing a model predictive controller. In contrast to existing impedance emulation schemes with cascaded feedback loops, the virtual impedance is included in the inner voltage control loop in order to achieve the highest possible bandwidth. Owing to constrained optimal control, this is achieved while respecting control variable constraints and inductor current safety limits. Experimental results show the effectiveness of the proposed battery impedance emulation scheme.\",\"PeriodicalId\":341659,\"journal\":{\"name\":\"2012 IEEE Vehicle Power and Propulsion Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Vehicle Power and Propulsion Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VPPC.2012.6422636\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Vehicle Power and Propulsion Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VPPC.2012.6422636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20

摘要

有了电池模拟器,开发工程师可以在测试台上测试电力驱动,而不需要昂贵的电池原型。此外,可以节省电池预处理的宝贵时间。然而,高质量的电池仿真是一个挑战,需要一个良好的电池模型和精确的仿真模型与可控的电源。采用基于局部模型网络的高保真非线性电池模型。这允许提取局部线性模型阻抗仿真与开关模型DC-DC转换器。将局部线性电池模型与变换器模型结合成预测模型,用于模型预测控制器的设计。与现有的级联反馈回路阻抗仿真方案相比,虚拟阻抗被包含在内电压控制环路中,以获得尽可能高的带宽。由于约束最优控制,这是在尊重控制变量约束和电感电流安全限制的情况下实现的。实验结果表明了所提出的电池阻抗仿真方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Battery impedance emulation for hybrid and electric powertrain testing
With battery emulators, development engineers can test electrical drives on testbeds without the need for costly battery prototypes. Furthermore, valuable time for battery pre-conditioning can be saved. However, high quality battery emulation is a challenge that requires a good battery model and accurate emulation of the model with a controllable power supply. A high-fidelity nonlinear battery model based on local model networks is used. This allows the extraction of local linear models for impedance emulation with a switch model DC-DC converter. Local linear battery models and a model of the converter are combined to a prediction model which is used for designing a model predictive controller. In contrast to existing impedance emulation schemes with cascaded feedback loops, the virtual impedance is included in the inner voltage control loop in order to achieve the highest possible bandwidth. Owing to constrained optimal control, this is achieved while respecting control variable constraints and inductor current safety limits. Experimental results show the effectiveness of the proposed battery impedance emulation scheme.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信