Simplification of physics-based electrochemical model for lithium ion battery on electric vehicle. Part II: Pseudo-two-dimensional model simplification and state of charge estimation

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Critical Review on the Battery State of Charge Estimation Methods for Electric Vehicles (2018, methodology): “The widely used electrochemical models for battery SoC estimation are the one-dimension (1D) model [32]–[34], the pseudo two-dimensional (P2D) model [35], the quasithree dimensional full order physical model [36] and the first principle model [31], among which the simplification of the P2D model, si”
A continuum of physics-based lithium-ion battery models reviewed (2022, methodology): “While some authors take an ad hoc approach, posing the model directly from a list of simplifying assumptions [11, 45, 46, 56, 82], others (particularly in the mathematical modelling community) use formal asymptotic methods to systematically derive the reduced order models directly from the DFN model”
Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries (2019, unknown): “In the past decade, Acronym definition EV Electric vehicle LIB Lithium-ion battery KF Kalman filter SOC State of charge BMS Battery management system ALS Autocovariance least square SOH State of health SOP State of power SOE State of energy SOF State of function OCV Open-circuit voltage ECM Electroc”