Optimal load sharing through balancing has the potential of increasing the lifetime and capacity of the lithiumion battery. This paper presents a model predictive control (MPC) approach for optimal load sharing for lithium-ion multi-battery systems in electric vehicles. The primary objective is the satisfaction of the motoring or regenerative load power demand. Secondary objectives are state of charge (SoC) and temperature balancing amongst battery units. An advanced electro-thermal model which includes a two-state thermal model is used, which leads to better performance in terms of temperature balancing and control. The proposed MPC controller, which reduces battery degradation, is validated through simulations under the urban dynamometer driving schedule. The results showed satisfactory power tracking, and SoC and temperature balancing.

Optimal load sharing in reconfigurable battery systems using an improved model predictive control method / Peprah, G. K.; Liberati, F.; Altaf, F.; Osei-Dadzie, G.; Di Giorgio, A.; Pietrabissa, A.. - (2021), pp. 979-984. (Intervento presentato al convegno 29th Mediterranean Conference on Control and Automation, MED 2021 tenutosi a Bari; Italia) [10.1109/MED51440.2021.9480237].

Optimal load sharing in reconfigurable battery systems using an improved model predictive control method

Liberati F.
;
Di Giorgio A.;Pietrabissa A.
2021

Abstract

Optimal load sharing through balancing has the potential of increasing the lifetime and capacity of the lithiumion battery. This paper presents a model predictive control (MPC) approach for optimal load sharing for lithium-ion multi-battery systems in electric vehicles. The primary objective is the satisfaction of the motoring or regenerative load power demand. Secondary objectives are state of charge (SoC) and temperature balancing amongst battery units. An advanced electro-thermal model which includes a two-state thermal model is used, which leads to better performance in terms of temperature balancing and control. The proposed MPC controller, which reduces battery degradation, is validated through simulations under the urban dynamometer driving schedule. The results showed satisfactory power tracking, and SoC and temperature balancing.
2021
29th Mediterranean Conference on Control and Automation, MED 2021
Charging (batteries); Dynamometers; Lithium-ion batteries; Model predictive control; Predictive control systems; Thermography (temperature measurement)
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Optimal load sharing in reconfigurable battery systems using an improved model predictive control method / Peprah, G. K.; Liberati, F.; Altaf, F.; Osei-Dadzie, G.; Di Giorgio, A.; Pietrabissa, A.. - (2021), pp. 979-984. (Intervento presentato al convegno 29th Mediterranean Conference on Control and Automation, MED 2021 tenutosi a Bari; Italia) [10.1109/MED51440.2021.9480237].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1567987
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