{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T14:29:43Z","timestamp":1779373783355,"version":"3.53.1"},"reference-count":39,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2016,8,19]],"date-time":"2016-08-19T00:00:00Z","timestamp":1471564800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51405374"],"award-info":[{"award-number":["51405374"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Postdoctoral Science Foundation of China","award":["2014M560763"],"award-info":[{"award-number":["2014M560763"]}]},{"name":"the Postdoctoral Science Special Foundation of China","award":["2016T90904"],"award-info":[{"award-number":["2016T90904"]}]},{"name":"the Fundamental Research Funds for the Central Universities"},{"name":"the Postdoctoral Science Foundation of Shaanxi"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Recently, State of energy (SOE) has become one of the most fundamental parameters for battery management systems in electric vehicles. However, current information is critical in SOE estimation and current sensor is usually utilized to obtain the latest current information. However, if the current sensor fails, the SOE estimation may be confronted with large error. Therefore, this paper attempts to make the following contributions: Current sensor fault detection and SOE estimation method is realized simultaneously. Through using the proportional integral observer (PIO) based method, the current sensor fault could be accurately estimated. By taking advantage of the accurate estimated current sensor fault, the influence caused by the current sensor fault can be eliminated and compensated. As a result, the results of the SOE estimation will be influenced little by the fault. In addition, the simulation and experimental workbench is established to verify the proposed method. The results indicate that the current sensor fault can be estimated accurately. Simultaneously, the SOE can also be estimated accurately and the estimation error is influenced little by the fault. The maximum SOE estimation error is less than 2%, even though the large current error caused by the current sensor fault still exists.<\/jats:p>","DOI":"10.3390\/s16081328","type":"journal-article","created":{"date-parts":[[2016,8,19]],"date-time":"2016-08-19T09:58:27Z","timestamp":1471600707000},"page":"1328","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["A Method to Simultaneously Detect the Current Sensor Fault and Estimate the State of Energy for Batteries in Electric Vehicles"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7255-9952","authenticated-orcid":false,"given":"Jun","family":"Xu","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"},{"name":"State Key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"},{"name":"State Key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiying","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"},{"name":"State Key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Binggang","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"},{"name":"State Key Laboratory for Manufacturing Systems Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2016,8,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"28385","DOI":"10.3390\/s151128385","article-title":"Application of novel lateral tire force sensors to vehicle parameter estimation of electric vehicles","volume":"15","author":"Nam","year":"2015","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1016\/j.apenergy.2015.05.102","article-title":"A comparative study and validation of state estimation algorithms for li-ion batteries in battery management systems","volume":"155","author":"Barillas","year":"2015","journal-title":"Appl. Energy"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"9313","DOI":"10.3390\/s111009313","article-title":"Hall-effect based semi-fast ac on-board charging equipment for electric vehicles","volume":"11","year":"2011","journal-title":"Sensors"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.jpowsour.2015.10.095","article-title":"The effect of average cycling current on total energy of lithium-ion batteries for electric vehicles","volume":"303","author":"Barai","year":"2016","journal-title":"J. Power Sour."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Chomat, M. (2015). New Applications of Electric Drives, InTech. [1st ed.]. Available online: http:\/\/www.intechopen.com\/books\/new-applications-of-electric-drives\/battery-management-system-for-electric-drive-vehicles-modeling-state-estimation-and-balancing.","DOI":"10.5772\/60584"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1109\/TSMCC.2010.2089979","article-title":"System identification and estimation framework for pivotal automotive battery management system characteristics","volume":"41","author":"Pattipati","year":"2011","journal-title":"IEEE Trans. Syst. Man Cybern. Part C Appl. Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1315","DOI":"10.1109\/TIE.2005.855671","article-title":"A new online state-of-charge estimation and monitoring system for sealed lead-acid batteries in telecommunication power supplies","volume":"52","author":"Kutluay","year":"2005","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1016\/j.jpowsour.2006.09.006","article-title":"The novel state of charge estimation method for lithium battery using sliding mode observer","volume":"163","author":"Kim","year":"2006","journal-title":"J. Power Sour."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2027","DOI":"10.1109\/TPEL.2008.924629","article-title":"Nonlinear state of charge estimator for hybrid electric vehicle battery","volume":"23","year":"2008","journal-title":"IEEE Trans. Power Electron."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1109\/TPEL.2009.2034966","article-title":"A technique for estimating the state of health of lithium batteries through a dual-sliding-mode observer","volume":"25","author":"Kim","year":"2010","journal-title":"IEEE Trans. Power Electron."},{"key":"ref_11","unstructured":"Ning, B., Xu, J., Cao, B., Wang, B., and Xu, G. (2015, January 15\u201317). A sliding mode observer soc estimation method based on parameter adaptive battery model. Proceedings of the CUE 2015 Applied Energy Symposium and Summit 2015: Low carbon cities and urban energy systems Low-carbon Cities and Urban Energy systems, Fuzhou, China."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.jpowsour.2004.02.031","article-title":"Extended kalman filtering for battery management systems of lipb-based hev battery packs: Part 1. Background","volume":"134","author":"Plett","year":"2004","journal-title":"J. Power Sour."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.jpowsour.2014.02.095","article-title":"Estimation of state-of-charge and state-of-power capability of lithium-ion battery considering varying health conditions","volume":"259","author":"Sun","year":"2014","journal-title":"J. Power Sour."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1016\/j.apenergy.2013.07.061","article-title":"A data-driven multi-scale extended kalman filtering based parameter and state estimation approach of lithium-ion olymer battery in electric vehicles","volume":"113","author":"Xiong","year":"2014","journal-title":"Appl. Energy"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.jpowsour.2013.03.158","article-title":"Online battery state of health estimation based on genetic algorithm for electric and hybrid vehicle applications","volume":"240","author":"Chen","year":"2013","journal-title":"J. Power Sour."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.ijepes.2014.06.017","article-title":"An online state of charge estimation method with reduced prior battery testing information","volume":"63","author":"Xu","year":"2014","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2726","DOI":"10.3390\/en6062726","article-title":"Soc based battery cell balancing with a novel topology and reduced component count","volume":"6","author":"Xu","year":"2013","journal-title":"Energies"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5065","DOI":"10.3390\/en7085065","article-title":"Evaluation of model based state of charge estimation methods for lithium-ion batteries","volume":"7","author":"Zou","year":"2014","journal-title":"Energies"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1614","DOI":"10.1109\/TVT.2013.2287375","article-title":"The state of charge estimation of lithium-ion batteries based on a proportional integral observer","volume":"63","author":"Xu","year":"2014","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.jpowsour.2015.01.145","article-title":"Electric vehicle state of charge estimation: Nonlinear correlation and fuzzy support vector machine","volume":"281","author":"Sheng","year":"2015","journal-title":"J. Power Sour."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1016\/j.ijepes.2013.05.038","article-title":"Estimation of the state of charge for a LFP battery using a hybrid method that combines a RBF neural network, an OLS algorithm and AGA","volume":"53","author":"Chang","year":"2013","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.apenergy.2014.01.066","article-title":"A new neural network model for the state-of-charge estimation in the battery degradation process","volume":"121","author":"Kang","year":"2014","journal-title":"Appl. Energy"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Renjian, F., Shuai, Z., and Xiaodong, L. (2013, January 16\u201318). On-line estimation of dynamic state-of-charge for lead acid battery based on fuzzy logic. Proceedings of the 2013 International Conference on Measurement, Information and Control, Harbin, China.","DOI":"10.1109\/MIC.2013.6758002"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.jpowsour.2014.07.107","article-title":"A method for state of energy estimation of lithium-ion batteries at dynamic currents and temperatures","volume":"270","author":"Liu","year":"2014","journal-title":"J. Power Sour."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.apenergy.2015.04.062","article-title":"A novel gaussian model based battery state estimation approach: State-of-energy","volume":"151","author":"He","year":"2015","journal-title":"Appl. Energy"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.apenergy.2014.08.081","article-title":"A method for joint estimation of state-of-charge and available energy of lifepo4 batteries","volume":"135","author":"Wang","year":"2014","journal-title":"Appl. Energy"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.jpowsour.2015.10.011","article-title":"An online model-based method for state of energy estimation of lithium-ion batteries using dual filters","volume":"301","author":"Dong","year":"2016","journal-title":"J. Power Sour."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.jpowsour.2015.11.087","article-title":"An adaptive remaining energy prediction approach for lithium-ion batteries in electric vehicles","volume":"305","author":"Wang","year":"2016","journal-title":"J. Power Sour."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"23119","DOI":"10.3390\/s141223119","article-title":"Online fault detection of permanent magnet demagnetization for ipmsms by nonsingular fast terminal-sliding-mode observer","volume":"14","author":"Zhao","year":"2014","journal-title":"Sensors"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"11027","DOI":"10.3390\/s150511027","article-title":"Current sensor fault diagnosis based on a sliding mode observer for PMSM driven systems","volume":"15","author":"Huang","year":"2015","journal-title":"Sensors"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/j.jpowsour.2014.06.052","article-title":"Model based condition monitoring in lithium-ion batteries","volume":"268","author":"Singh","year":"2014","journal-title":"J. Power Sour."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"973","DOI":"10.1109\/TIE.2008.2010095","article-title":"Fault diagnosis of time-varying parameter systems with application in MEMS LCRs","volume":"56","author":"Izadian","year":"2009","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1109\/TCST.2013.2239296","article-title":"Simultaneous fault isolation and estimation of lithium-ion batteries via synthesized design of luenberger and learning observers","volume":"22","author":"Wen","year":"2014","journal-title":"IEEE Trans. Control Syst. Technol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1109\/TIE.2014.2336599","article-title":"Adaptive nonlinear model-based fault diagnosis of Li-ion Batteries","volume":"62","author":"Sidhu","year":"2015","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.jpowsour.2013.03.129","article-title":"Prognostics of lithium-ion batteries based on relevance vectors and a conditional three-parameter capacity degradation model","volume":"239","author":"Wang","year":"2013","journal-title":"J. Power Sour."},{"key":"ref_36","unstructured":"Kozlowski, J.D. (2003, January 8\u201315). Electrochemical cell prognostics using online impedance measurements and model-based data fusion techniques. Proceedings of the 2003 IEEE Aerospace Conference, Big Sky, MT, USA."},{"key":"ref_37","first-page":"1","article-title":"Sensor fault detection, isolation, and estimation in Lithium-ion batteries","volume":"99","author":"Dey","year":"2016","journal-title":"IEEE Trans. Control Syst. Technol."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Liu, Z., Ahmed, Q., Rizzoni, G., and He, H. (2014, January 22\u201324). Fault detection and isolation for Lithium-ion battery system using structural analysis and sequential residual generation. Proceedings of the ASME 2014 Dynamic Systems and Control Conference, San Antonio, Texas, USA.","DOI":"10.1115\/DSCC2014-6101"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.jpowsour.2013.01.094","article-title":"A new method to estimate the state of charge of lithium-ion batteries based on the battery impedance model","volume":"233","author":"Xu","year":"2013","journal-title":"J. Power Sour."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/8\/1328\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:28:47Z","timestamp":1760210927000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/8\/1328"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,8,19]]},"references-count":39,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2016,8]]}},"alternative-id":["s16081328"],"URL":"https:\/\/doi.org\/10.3390\/s16081328","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,8,19]]}}}