Smart Battery Technology for Lifetime Improvement
Applications of lithium-ion batteries are widespread, ranging from electric vehicles to energy storage systems. In spite of nearly meeting the target in terms of energy density and cost, enhanced safety, lifetime, and second-life applications, there remain challenges. As a result of the difference b...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-10-01
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| Series: | Batteries |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-0105/8/10/169 |
| _version_ | 1827651592034189312 |
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| author | Remus Teodorescu Xin Sui Søren B. Vilsen Pallavi Bharadwaj Abhijit Kulkarni Daniel-Ioan Stroe |
| author_facet | Remus Teodorescu Xin Sui Søren B. Vilsen Pallavi Bharadwaj Abhijit Kulkarni Daniel-Ioan Stroe |
| author_sort | Remus Teodorescu |
| collection | DOAJ |
| description | Applications of lithium-ion batteries are widespread, ranging from electric vehicles to energy storage systems. In spite of nearly meeting the target in terms of energy density and cost, enhanced safety, lifetime, and second-life applications, there remain challenges. As a result of the difference between the electric characteristics of the cells, the degradation process is accelerated for battery packs containing many cells. The development of new generation battery solutions for transportation and grid storage with improved performance is the goal of this paper, which introduces the novel concept of Smart Battery that brings together batteries with advanced power electronics and artificial intelligence (AI). The key feature is a bypass device attached to each cell that can insert relaxation time to individual cell operation with minimal effect on the load. An advanced AI-based performance optimizer is trained to recognize early signs of accelerated degradation modes and to decide upon the optimal insertion of relaxation time. The resulting pulsed current operation has been proven to extend lifetime by up to 80% in laboratory aging conditions. The Smart Battery unique architecture uses a digital twin to accelerate the training of performance optimizers and predict failures. The Smart Battery technology is a new technology currently at the proof-of-concept stage. |
| first_indexed | 2024-03-09T20:41:48Z |
| format | Article |
| id | doaj.art-5be2ebf4ca1742d59648527fa354c15b |
| institution | Directory Open Access Journal |
| issn | 2313-0105 |
| language | English |
| last_indexed | 2024-03-09T20:41:48Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Batteries |
| spelling | doaj.art-5be2ebf4ca1742d59648527fa354c15b2023-11-23T22:55:15ZengMDPI AGBatteries2313-01052022-10-0181016910.3390/batteries8100169Smart Battery Technology for Lifetime ImprovementRemus Teodorescu0Xin Sui1Søren B. Vilsen2Pallavi Bharadwaj3Abhijit Kulkarni4Daniel-Ioan Stroe5AAU Energy, Aalborg University, 9220 Aalborg, DenmarkAAU Energy, Aalborg University, 9220 Aalborg, DenmarkDepartment of Mathematical Sciences, Aalborg University, 9220 Aalborg, DenmarkAAU Energy, Aalborg University, 9220 Aalborg, DenmarkAAU Energy, Aalborg University, 9220 Aalborg, DenmarkAAU Energy, Aalborg University, 9220 Aalborg, DenmarkApplications of lithium-ion batteries are widespread, ranging from electric vehicles to energy storage systems. In spite of nearly meeting the target in terms of energy density and cost, enhanced safety, lifetime, and second-life applications, there remain challenges. As a result of the difference between the electric characteristics of the cells, the degradation process is accelerated for battery packs containing many cells. The development of new generation battery solutions for transportation and grid storage with improved performance is the goal of this paper, which introduces the novel concept of Smart Battery that brings together batteries with advanced power electronics and artificial intelligence (AI). The key feature is a bypass device attached to each cell that can insert relaxation time to individual cell operation with minimal effect on the load. An advanced AI-based performance optimizer is trained to recognize early signs of accelerated degradation modes and to decide upon the optimal insertion of relaxation time. The resulting pulsed current operation has been proven to extend lifetime by up to 80% in laboratory aging conditions. The Smart Battery unique architecture uses a digital twin to accelerate the training of performance optimizers and predict failures. The Smart Battery technology is a new technology currently at the proof-of-concept stage.https://www.mdpi.com/2313-0105/8/10/169Smart Batteryartificial intelligencepulse currentlifetime extensionsecond-life applications |
| spellingShingle | Remus Teodorescu Xin Sui Søren B. Vilsen Pallavi Bharadwaj Abhijit Kulkarni Daniel-Ioan Stroe Smart Battery Technology for Lifetime Improvement Batteries Smart Battery artificial intelligence pulse current lifetime extension second-life applications |
| title | Smart Battery Technology for Lifetime Improvement |
| title_full | Smart Battery Technology for Lifetime Improvement |
| title_fullStr | Smart Battery Technology for Lifetime Improvement |
| title_full_unstemmed | Smart Battery Technology for Lifetime Improvement |
| title_short | Smart Battery Technology for Lifetime Improvement |
| title_sort | smart battery technology for lifetime improvement |
| topic | Smart Battery artificial intelligence pulse current lifetime extension second-life applications |
| url | https://www.mdpi.com/2313-0105/8/10/169 |
| work_keys_str_mv | AT remusteodorescu smartbatterytechnologyforlifetimeimprovement AT xinsui smartbatterytechnologyforlifetimeimprovement AT sørenbvilsen smartbatterytechnologyforlifetimeimprovement AT pallavibharadwaj smartbatterytechnologyforlifetimeimprovement AT abhijitkulkarni smartbatterytechnologyforlifetimeimprovement AT danielioanstroe smartbatterytechnologyforlifetimeimprovement |