TY - GEN
T1 - Design automation for battery systems
AU - Narayanaswamy, Swaminathan
AU - Park, Sangyoung
AU - Steinhorst, Sebastian
AU - Chakraborty, Samarjit
N1 - Publisher Copyright:
© 2018 ACM.
PY - 2018/11/5
Y1 - 2018/11/5
N2 - High power Lithium-Ion (Li-Ion) battery packs used in stationary Electrical Energy Storage (EES) systems and Electric Vehicle (EV) applications require a sophisticated Battery Management System (BMS) in order to maintain safe operation and improve their performance. With the increasing complexity of these battery packs and their demand for shorter time-to-market, decentralized approaches for battery management, providing a high degree of modularity, scalability and improved control performance are typically preferred. However, manual design approaches for these complex distributed systems are time consuming and are error-prone resulting in a reduced energy efficiency of the overall system. Here, special design automation techniques considering all abstraction-levels of the battery system are required to obtain highly optimized battery packs. This paper presents from a design automation perspective the recent advances in the domain of battery systems that are a combination of the electrochemical cells and their associated management modules. Specifically, we classify the battery systems into three abstraction levels, cell-level (battery cells and their interconnection schemes), module-level (sensing and charge balancing circuits) and pack-level (computation and control algorithms). We provide an overview of challenges that exist in each abstraction layer and give an outlook towards future design automation techniques that are required to overcome these limitations.
AB - High power Lithium-Ion (Li-Ion) battery packs used in stationary Electrical Energy Storage (EES) systems and Electric Vehicle (EV) applications require a sophisticated Battery Management System (BMS) in order to maintain safe operation and improve their performance. With the increasing complexity of these battery packs and their demand for shorter time-to-market, decentralized approaches for battery management, providing a high degree of modularity, scalability and improved control performance are typically preferred. However, manual design approaches for these complex distributed systems are time consuming and are error-prone resulting in a reduced energy efficiency of the overall system. Here, special design automation techniques considering all abstraction-levels of the battery system are required to obtain highly optimized battery packs. This paper presents from a design automation perspective the recent advances in the domain of battery systems that are a combination of the electrochemical cells and their associated management modules. Specifically, we classify the battery systems into three abstraction levels, cell-level (battery cells and their interconnection schemes), module-level (sensing and charge balancing circuits) and pack-level (computation and control algorithms). We provide an overview of challenges that exist in each abstraction layer and give an outlook towards future design automation techniques that are required to overcome these limitations.
KW - batteries
KW - battery management systems
KW - design automation
UR - http://www.scopus.com/inward/record.url?scp=85058174269&partnerID=8YFLogxK
U2 - 10.1145/3240765.3243469
DO - 10.1145/3240765.3243469
M3 - Conference contribution
AN - SCOPUS:85058174269
T3 - IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
BT - 2018 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2018 - Digest of Technical Papers
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 37th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2018
Y2 - 5 November 2018 through 8 November 2018
ER -