Battery Adaptive Observer for a Single-Particle Model With Intercalation-Induced Stress

Abstract

Battery electrode particle fracture due to stress generation is a critical mechanism causing capacity fade, and thus reducing battery life. This paper develops a nonlinear adaptive observer for lithium-ion battery state of charge (SOC), electrode particle stress, and solid phase diffusivity estimation using a high-fidelity coupled single particle-mechanical stress model, where the stress submodel captures stress development during lithium-ion intercalation and deintercalation. Simultaneous state and parameter estimation based on coupled single particle and mechanical stress model is extremely challenging because the coupled model is given by highly nonlinear partial differential equations. We address this problem by reducing the coupled model to a nonlinear finite dimensional system. The key novelty of this paper is a nonlinear internal state and parameter estimation methodology, from which the internal stress and the state of health-related parameters are monitored from real-time electric current and terminal voltage measurements. Numerical studies on simulation and experimental data have been conducted to illustrate the performance of the proposed estimation scheme.

Adaptive relative velocity estimation algorithm for autonomous mobile robots using the measurements on acceleration and relative distance

“…Adaptive techniques have been already developed as controller methods [19][20][21][22][23][24] as well as observer algorithms [25][26][27][28] in diverse applications. [29][30][31][32] Here, an adaptive technique is incorporated in a solution for problem of relative velocity estimation for aerial AMRs. The estimation algorithm needs the measurement on the relative distance and the vector of relative acceleration.…”

“…Recalling the above limitations, an adaptive relative velocity estimation (ARVE) algorithm is presented in the current article. Adaptive techniques have been already developed as controller methods as well as observer algorithms in diverse applications . Here, an adaptive technique is incorporated in a solution for problem of relative velocity estimation for aerial AMRs.…”

State of health prediction of lithium-ion batteries based on machine learning: Advances and perspectives

“…Currently, some researches are focused on state estimation of lithium-ion batteries by establishing a simplified pseudo-two-dimensional (P2D) EM ( Feng et al., 2020a ). Meanwhile, the single-particle model (SPM) with less computation intensity and acceptable precision has also been widely exploited in SOH estimation ( Zhang et al., 2020a ). Liu et al.…”

An Optimal Fast-Charging Strategy for Lithium-Ion Batteries via an Electrochemical–Thermal Model with Intercalation-Induced Stresses and Film Growth

“…Considering the effects of intercalation-induced stress helps us to investigate the fast-charging scheme to reduce the electrode particle fracture and thus prolong the lifetime of the lithium-ion battery. The intercalation-induced stresses are composed of radial stress σ r and tangential stress σ t , which are dependent of the lithium concentration [22]:…”