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The reuse of retired electric vehicle batteries in grid energy storage offers environmental and economic benefits. This study concentrates on health monitoring algorithms for retired batteries deployed in grid storage. Over 15 months of testing, we collect, analyze, and publicize a dataset of second-life batteries, implementing a cycling protocol simulating grid energy storage load profiles within a 3-4 V voltage window. Four machine-learning-based health estimation models, relying on online-accessible features and initial capacity, are compared, with the selected model achieving a mean absolute percentage error below 2.3% on test data. Additionally, an adaptive online health estimation algorithm is proposed by integrating a clustering-based method, thus limiting estimation errors during online deployment. These results showcase the feasibility of repurposing retired batteries for second-life applications. Based on obtained data and power demand, these second-life batteries exhibit potential for over a decade of grid energy storage use., Comment: 16 pages, 8 figures

A key challenge that is currently hindering the widespread use of retired electric vehicle (EV) batteries for second-life (SL) applications is the ability to accurately estimate and monitor their state of health (SOH). Second-life battery systems can be sourced from different battery packs with lack of knowledge of their historical usage. To tackle the in-the-field use of SL batteries, this paper introduces an online adaptive health estimation approach with guaranteed bounded-input-bounded-output (BIBO) stability. This method relies exclusively on operational data that can be accessed in real time from SL batteries. The effectiveness of the proposed approach is shown on a laboratory aged experimental data set of retired EV batteries. The estimator gains are dynamically adapted to accommodate the distinct characteristics of each individual cell, making it a promising candidate for future SL battery management systems (BMS2)., Comment: Update the paper within the 10-page limit

Due to the increasing volume of Electric Vehicles in automotive markets and the limited lifetime of onboard lithium-ion batteries (LIBs), the large-scale retirement of LIBs is imminent. The battery packs retired from Electric Vehicles still own 70%-80% of the initial capacity, thus having the potential to be utilized in scenarios with lower energy and power requirements to maximize the value of LIBs. However, spent batteries are commonly less reliable than fresh batteries due to their degraded performance, thereby necessitating a comprehensive assessment from safety and economic perspectives before further utilization. To this end, this paper reviews the key technological and economic aspects of second-life batteries (SLBs). Firstly, we introduce various degradation models for first-life batteries and identify an opportunity to combine physics-based theories with data-driven methods to establish explainable models with physical laws that can be generalized. However, degradation models specifically tailored to SLBs are currently absent. Therefore, we analyze the applicability of existing battery degradation models developed for first-life batteries in SLB applications. Secondly, we investigate fast screening and regrouping techniques and discuss the regrouping standards for the first time to guide the classification procedure and enhance the performance and safety of SLBs. Thirdly, we scrutinize the economic analysis of SLBs and summarize the potentially profitable applications. Finally, we comprehensively examine and compare power electronics technologies that can substantially improve the performance of SLBs, including high-efficiency energy transformation technologies, active equalization technologies, and technologies to improve reliability and safety.

With more inverter-based resources (IBRs), our power systems have lower frequency nadirs following N-1 contingencies, and undesired under-frequency load shedding (UFLS) can occur. To address this challenge, IBRs can be programmed to provide at least three types of fast frequency response (FFR), e.g., step response, proportional response (P/f droop response), and derivative response (synthetic inertia). However, these heterogeneous FFR challenge the study of power system frequency dynamics. Thus, this paper develops an analytical frequency nadir prediction method that allows for the consideration of all three potential forms of FFR provided by IBRs. The proposed method provides fast and accurate frequency nadir estimation after N-1 generation tripping contingencies. Our method is grounded on the closed-form solution for the frequency nadir, which is solved from the second-order system frequency response model considering the governor dynamics and three types of FFR. The simulation results in the IEEE 39-bus system with different types of FFR demonstrate that the proposed method provides an accurate and fast prediction of the frequency nadir under various disturbances.

This paper investigates a new method to model and control variable-frequency power converters in a switching-synchronized sampled-state space for cycle-by-cycle digital control. There are a number of significant benefits in comparison to other methods including fast dynamic performance together with ease of design and implementation. Theoretical results are presented and verified through hardware, and simulations of a current-mode buck converter with constant on-time and a current-mode boost converter with constant off-time. Dynamic voltage scaling for microprocessors and LiDAR are among the applications that can benefit.

This article is the second part of a paper series about interference in extremum (i.e., peak or valley) current-mode control, which applies to both fixed and variable switching frequency power converters. Specifically, this part presents three control conditioning methods that mitigate the adverse effect of interference. These methods are new ways to use: (i) slope compensation; (ii) low-pass filtering; and (iii) the phenomenon of comparator-overdrive-delay, for control conditioning. The stability criterion, closed-loop dynamics, and transient performance are derived with mathematical rigor for each method. The design tradeoffs are illustrated, discussed, and compared. The effectiveness of all three methods are demonstrated and validated in hardware using a power converter operating at multi-MHz switching frequencies.

Current-mode control is one of the most popular controller strategies for power converters. With the advent of wide bandgap devices including GaN and SiC, higher switching frequencies have become more viable at higher power because of lower switching losses. However, the advantage of higher switching frequency for faster, higher bandwidth control is squandered because of current sensor interference. We present a framework for characterizing and analyzing this interference as uncertainties to the controller model. These uncertainties introduce additional dynamics and nonlinearity that can result in instability and poor transient performance of the current control loop. In this paper, we provide a model framework based on a new control conditioning approach that guarantees global stability and a strategy for optimizing transient performance. In Part II of this paper series, we present the analysis, design, and hardware validation of three effective solutions.

Comparator-overdrive-delay conditioning is a new control conditioning approach for high-frequency current-mode control. No existing literature rigorously studies the effect of the comparator overdrive delay on the current-mode control. The results in this paper provide insights into the mechanism of comparator-overdrive-delay conditioning.

The low-pass filter is a classic control conditioning approach for high-frequency current-mode control. However, no existing literature discusses the large-signal stability criterion for the current-mode control with low-pass filters. This paper provides a mathematically rigorous large-signal stability criterion. The result can directly benefit the practical engineering implementation of the low-pass filter in high-frequency current-mode control.

Stability guarantees are critical for cycle-by-cycle controlled dc-dc converters in consumer electronics and energy storage systems. Traditional stability analysis on cycle-by-cycle dc-dc converters is incomplete because the inductor current ramps are considered fixed; but instead, inductor ramps are not fixed because they are dependent on the output voltage in large-signal transients. We demonstrate a new large-signal stability theory that treats cycle-by-cycle controlled dc-dc converters as a particular type of feedback interconnection system. An analytical and practical stability criterion is provided based on this system. The criterion indicates that the L/R and RC time constants are the design parameters that determine the amount of coupling between the current ramp and the output voltage., Comment: typos corrected, references added, title, abstract, and introduction revised, results unchanged

The explosive growth of electric vehicles (EVs) is leading to a surge in retired EV batteries, which are typically recycled despite having nearly 80% available capacity. Repurposing automotive batteries for second-use battery energy storage systems (2-BESS) has both economical and environmental benefits. The challenge with second-use batteries is the heterogeneity in their state of health. This paper introduces a new strategy to optimize 2-BESS performance despite the heterogeneity of individual batteries while reducing the cost of power conversion. In this paper, the statistical distribution of the power heterogeneity in the supply of batteries is used to optimize the choice of power converters and design the power flow within the battery energy storage system (BESS) to optimize power capability. By leveraging a new lite-sparse hierarchical partial power processing (LS-HiPPP) approach, we study how a hierarchy in partial power processing (PPP) partitions power converters to significantly reduce converter ratings, process less power to achieve high system efficiency with lower cost (lower efficiency) converters, and take advantage of economies of scale by requiring only a minimal number of sets of identical converters. Our results demonstrate that LS-HiPPP architectures offer the best tradeoff between battery utilization and converter cost and have higher system efficiency than conventional partial power processing (C-PPP) in all cases., Comment: typos corrected, references added, title, abstract and introduction revised, DOI updated, results unchanged

The heterogeneity in pack voltages and capacity of aged packs limits the performance and economic viability of second-use battery energy storage systems (2-BESS) due to issues of reliability and available energy. Overcoming these limitations could enable extended use of batteries and improve the environmental impacts of electric vehicles by reducing the number of batteries produced. This paper compares Lite-Sparse Hierarchical Partial Power Processing (LS-HiPPP), a new method for power processing in 2-BESS, to conventional power processing architectures using a stochastic EV charging plaza model. This method for performance evaluation allows a fair comparison among power processing architectures for 2-BESS. Results show that LS-HiPPP increases the battery energy utilization to 94% as compared to 78% for conventional partial power processing (C-PPP) and 23% for full power processing. These results were obtained with 25% heterogeneity in individual battery capacities and 20% power processing within the 2-BESS. Derating and captured value are two derived performance metrics for comparing LS-HiPPP and C-PPP in this work. The derating for LS-HiPPP is 84.3% in comparison to 63.1% for C-PPP. The captured value for LS-HiPPP is 79.8% versus 51% for C-PPP., Comment: typos corrected, references added, several sections from the previous version were omitted because it is out of scope for the journal submission, title, abstract and introduction revised, results unchanged

The increasing adoption of power electronic devices may lead to large disturbance and destabilization of future power systems. However, stability criteria are still an unsolved puzzle, since traditional small-signal stability analysis is not applicable to power electronics-enabled power systems when a large disturbance occurs, such as a fault, a pulse power load, or load switching. To address this issue, this paper presents for the first time the rigorous derivation of the sufficient criteria for large-signal stability in DC microgrids with distributed-controlled DC-DC power converters. A novel type of closed-loop converter controllers is designed and considered. Moreover, this paper is the first to prove that the well-known and frequently cited Brayton-Moser mixed potential theory (published in 1964) is incomplete. Case studies are carried out to illustrate the defects of Brayton-Moser mixed potential theory and verify the effectiveness of the proposed novel stability criteria.

This paper develops the singular perturbation theory for a particular discrete-time nonlinear system which models the saturating inductor buck converter using cycle-by-cycle digital control.

In this paper, we illustrate a new correct-by-construction switching controller for a power converter with event-triggered measurements. The event-triggered measurement scheme is beneficial for high frequency power converters because it requires relatively low-speed sampling hardware and is immune to unmodeled switching transients. While providing guarantees on the closed-loop system behavior is crucial in this application, off-the-shelf abstraction-based techniques cannot be directly employed to synthesize a controller in this setting because controller cannot always get instantaneous access to the current state. As a result, the switching action has to be based on slightly out-of-date measurements. To tackle this challenge, we introduce the out-of-date measurement as an extra state variable and project out the inaccessible real state to construct a belief space abstraction. The properties preserved by this belief space abstraction are analyzed. Finally, an abstraction-based synthesis method is applied to this abstraction. We demonstrate the controller on a constant on-time buck voltage regulator plant with an event-triggered sampler. The simulation verifies the effectiveness of our controller., Comment: To appear in the Proc. American Control Conference (ACC), Philadelphia, PA, July 2019