Optimal Health-aware Charging Protocol for Lithium-ion Batteries: A Fast Model Predictive Control Approach. Issue 7 (2016)

• Record Type: Journal Article
• Authors: Torchio, M.; Magni, L.; Braatz, R.D.; Raimondo, D.M.
• Is Part Of: IFAC-PapersOnLine. Volume 49:Issue 7(2016)
• Page Start: 827
• Page End: 832
• Publication Date: 2016
• Subjects: Advanced Battery Management Systems -- health-aware control of Li-ion batteries -- model predictive control; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2016.07.292
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Lithium-ion batteries are widely used in industry to supply different portable applications. Their management is handled by Battery Management Systems (BMSs), which are intended to ensure good performance (such as minimum charging time) while simultaneously minimizing safety risks. The use of accurate mathematical models can help in achieving such goals. The first-principles pseudo-two dimensional (P2D) model is one of the mostly used models for simulation but rarely used in design of BMSs. This model, together with a description of the capacity fade mechanisms occurring during battery operations, is used to design health-aware BMS strategies. A Model Predictive Control (MPC) scheme based on a linearized version of the P2D model is proposed in order to track a reference value of the State of Charge (SOC), while taking into account the aging dynamics of the system as well as temperature and voltage constraints. Simulations show the effectiveness of the approach: the tuning of the control parameters allows controlled operation with different tradeoffs between charging time and battery lifetime enhancement.