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Accurate modeling of electrochemical batteries is of major concern in designing the control system of Energy Storage Systems (ESS). In particular, a precise estimation of State of Charge (SOC) and State of Health (SOH) parameters strongly affects the full exploitation of battery energy potential in real applications. In this paper a novel real-time estimation method is presented representing a good...
Lithium (Li) ion cells suffer from significant performance degradation at sub-zero temperatures. This paper presents a Predictive Control based technique that exploits the increased internal resistance of Li-ion cells to improve the power capability of Li-ion cells operating at sub-zero temperatures. The current is shaped as bi-directional pulses to minimize total energy discharge and adverse side...
Onboard Hybrid Electric Vehicles (HEV) and Battery Electric Vehicles (BEV), the Battery Management System (BMS) is of critical importance to ensure safe and reliable use of the electrical energy stored inside Li-ion batteries until the End-Of-Life (EOL) of the electrochemical system. At any time, the BMS must indicate the allowable current limits for charge and discharge (CMI: Charge Maximal Intensity...
Lithium ion (Li-ion) batteries are the standard choice for many applications; but their behavior is complex. In order to safely and efficiently exploit their advantages, advanced model-based Battery Management Systems (BMS) are required. This paper introduces a computationally efficient, control-oriented model for a Li-ion cell. The model, by augmenting the classical Randle model with diffusive dynamics,...
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