Estimation of electrode state health (eSOH) is essential to understanding battery degradation status in detail. This accomplished by considering capacity and a utilization range as eSOH parameters. In this paper, we propose novel combination two estimation approaches (i.e. voltage fitting differential analysis). By utilizing peak information the curve, proposed method can separate individual electrode's contributions from full-cell voltage. separation allows identify changes positive...

In this study, we propose a new capacity estimation scheme for various aging states of lithium-ion batteries based on an inverted bottleneck network (IBN) that learns electrochemical knowledge. Most existing schemes employ simple models have limitations in accuracy because they cannot reflect the complex inside batteries. An model is sufficiently sophisticated to estimate accurately; however, it computationally expensive. Therefore, transfer knowledge deals with physicochemical behavior...

Accurate prediction of the battery electrochemical dynamics is important to avoid undesired operation under aggressive driving. This paper proposes a power management strategy considering Li-ion concentration in electrodes prevent excessive charging and discharging. The proposed approach adjusts allowable limits through feedback estimated electrode-averaged information. An advanced hybrid electric vehicle (HEV) split constructed implementing model with diffusion capture dynamic behavior...

Advanced battery management system, which leverages an in-depth understanding of the state health, can improve efficiently and safely. To this end, we introduce electrode-level health (eSOH) estimation problem with open-circuit voltage (OCV) data. In real-world applications, collecting full-range OCV data is difficult since not deeply discharged. When limited, accuracy deteriorates. article, quantify uncertainty electrode parameter partial based on Cramer-Rao bound confidence interval. By...

It is essential to understand the state-of-health (SOH) of individual electrode avoid accelerating degradation Li-ion battery. Electrode SOH can be quantified based on estimating capacity and utilization range each electrode. Here, we introduce two methods: i) voltage fitting (VF) ii) peak alignment (PA), compare their ability estimate parameters. Both methods assume half-cell open-circuit potentials (OCPs) are invariant functions stoichio-metric states with cell aging, which make accuracy...

This paper proposes a reduced Li-ion battery model for design optimization and control by implementing the electrode-averaged diffusion dynamics uneven discretization of particle radius fast computation accurate prediction Lithium intercalation dynamics. First, unevenly discretized is constructed from ordinary differential equation (ODE) derived in model. Then, constrained problems with multi-objectives are formulated to find optimal discretization. The cost function evaluated under wide...

This paper proposes a battery power management strategy using the estimated lithium-ion concentration in electrodes to prevent over-charging and over-discharging under aggressive driving conditions. Excessive operation is moderated by adjusting allowable limits through feedback of information on electrode-averaged extended Kalman filter. Uneven discretization radii solid electrode particles used filter reduce computation effort. Safe with relatively small size possible proposed preventing...

This paper develops a tip-tilt motion controller of fast steering mirror (FSM) in the Giant Magellan telescope (GMT). A mathematical model system FSM is derived, and then based on this model, stability analysis carried out. heuristic adaptive designed for control with modeling error. The consists two different adaptations such as initial adaptation at steady state errors. Through numerical simulations, validity illustrated. After that addresses several practical issues like disturbance from...

This paper proposes an approach to develop reduced-order electrochemical battery models for controls. The are derived from detailed models, which combine ionic and electronic processes in the level of active material particles, through a significant model reduction with order hundreds or more. is possible understanding process cells. developed can capture most key dynamics cell few state variables. validated using real-world vehicle test data, consist both charge depleting (CD) sustaining...

Model-based thermal management enables sophisticated battery temperature control due to the availability of information among and inside cells. This paper proposes a reduced-order modeling approach by combining pre-calculated distribution in steady state approximated transient responses from multi-dimensional full-order models. The number states is reduced an order hundreds, developed model can predict dynamics with errors within 0.2 °C compared full simulation results under real-world driving cycle.

Prediction of battery system responses and capability for next few seconds can provide key information to use hardware effectively. The prediction performance will be much improved, when models capture the real as accurate possible. Equivalent circuit (ECMs) have been used control purpose due their proper balance between computational efficiency accuracy. limitations ECMs efficiently compensated through real-time model parameter estimation. Further enhancement is possible by improving...

The aim of this paper is the reconstruction a smooth surface from an unorganized point cloud sampled by closed surface, with preservation geometric shapes, without any further information other than cloud. Implicit neural representations (INRs) have recently emerged as promising approach to reconstruction. However, quality existing methods relies on ground truth implicit function values or normal vectors. In paper, we show that proper supervision partial differential equations and...