Optimal charging for general equivalent electrical battery model, and battery life management

Abstract

The contributions of this paper are threefold. First, we present the linear quadratic solution to optimally charge a Li-ion battery in a general form. Although the battery model considered here is a circuit comprised of an open-circuit voltage (OCV), a series resistance, and an RC circuit, the methodology is applicable to any electrical circuit model of a battery. A combination of different cost functions is considered including: time-to-charge, energy loss, and temperature rise index. We discuss the effect of different weightings in the cost functions on the current and voltage profiles. Second, we present two models for normalized battery capacity as a function of the number of cycles and two charge control parameters, viz., maximum terminal voltage of the battery and maximum charge current. These models are compared to a bi-exponential capacity model. The effectiveness of the proposed models for forecasting the battery capacity is validated using the experimental data. Third, these models are used for battery life management by developing an optimal charging parameter selection method which provides the best setpoint values for the control variables to achieve a pre-specified desired "useful cycle life" while attaining the fastest possible time-to-charge. The proposed optimal charging parameter selection method is illustrated via numerical results.

Fast computational framework for optimal life management of lithium ion batteries

“…This is critical, as the pattern of degradation of a LiB changes during cycling. Abdollahi et al 42,43 have developed a control variable-dependent model for predicting the cycle life of battery and utilized it for determining the optimal maximum charging current and maximum terminal voltage that achieve a prescribed useful cycle life while achieving the fastest possible time to charge. However, the utilization of this model requires the availability of extensive experimental information.…”

A Simple Distribution Energy Tariff under the Penetration of DG

“…A first element to be defined is the functioning of the ESS. Although numerous approaches define optimal battery charge/discharge policies, such policies are more focused on preserving the chemical life of batteries and other aspects related to operating concerns [24]. The proposed model for storage is simple enough to capture the conservation of energy in a storage device as follows: is the amount of energy deployed by the storage system (if E STRG i,k < 0, the storage system is charged from the grid).…”

Cranking Capability Estimation Algorithm Based on Modeling and Online Update of Model Parameters for Li-Ion SLI Batteries

“…(5) Calculate R s1 (t k ) and L s (t k ) by solving a simultaneous equation between Equations (18) and (19).…”

“…In conventional studies, many ECMs for Li-ion batteries and ECM parameter identification methods have been proposed for battery management system (BMS) applications: the high-order resistor-capacitor (RC)-ladder model, Randle model, Thevenin model, and partial differential equations model [15][16][17][18][19][20][21]. These models are sufficiently reliable for general state estimation algorithms, such as state-of-charge (SOC) and state-of-health (SOH), but not directly applicable to SOF, which is required to simulate the fast voltage response.…”

“…Figure 2a shows a conventional ECM based on the 1st RC-ladder, which consists of R s , R 1 , and C 1 . R s denotes the internal resistance of the battery and describes the ohmic voltage drop generated by an instantaneous change in the terminal current [15][16][17][18][19][20][21]. Moreover, the 1st RC-ladder simulates the polarization voltage as the curve of the exponential function, of which the time constant is determined by R 1 and C 1 .…”