arXiv subjects

Xiaofan Cui

Publications and source records attributed to Xiaofan Cui.

At least 19 recordsLinked to original sources

arXiv2026

Decentralized Attack-Resilient CLF-Based Control of Nonlinear DC Microgrids under FDI Attacks

The growing deployment of nonlinear, converter interfaced distributed energy resources (DERs) in DC microgrids demands decentralized controllers that remain stable and resilient under a wide range of cyber-physical attacks and disturbances. Traditional droop or linearized control methods lack resilience and scalability, especially when the system operates in its nonlinear region or faces diverse false-data-injection (FDI) attacks on control inputs. In this work, we develop a Decentralized Attack-Resilient Control Lyapunov Function (AR-CLF) based Quadratic Program (QP) control framework for nonlinear DC microgrids that ensures large-signal stability in a fully decentralized manner. Built upon the port-Hamiltonian representation, the proposed controller dynamically compensates diverse attacks including exponentially unbounded control-input perturbations beyond the bounded-attack regime commonly assumed in existing methods, through an adaptive resilience term, without requiring global information. Simulations validate that the AR-CLF based QP controller achieves superior stability and resilience against unbounded attacks, paving the way for scalable, attack-resilient, and physically consistent control of next-generation DC microgrids.

eess.SY↗

arXiv2025

Decentralized Safety-Critical Control of Resilient DC Microgrids with Large-Signal Stability Guarantees

The increasing penetration of distributed energy resources and power-electronics interfaces in DC microgrids, coupled with rising cyber threats, necessitates primary controllers that are provably safe, cyber-resilient, and practical. The increasing penetration of distributed energy resources and power-electronics interfaces in DC microgrids, coupled with rising cyber threats, necessitates primary controllers that are provably safe, cyber-resilient, and practical. Conventional droop-based methods remain prevalent due to their simplicity, yet their design is largely empirical and conservative, lacking rigorous guarantees. Advanced strategies improve certain aspects, but often sacrifice scalability, robustness, or formal safety. In this work, we propose a Distributed Safety-Critical Controller (DSCC) that systematically integrates global stabilization with formal safety guarantees in a fully decentralized manner. Leveraging control barrier functions and the port-Hamiltonian system theory, the DSCC achieves scalable safe stabilization while preserving real-time implementability. High-fidelity switched-circuit simulations validate the controller's advantages under various contingencies. This framework paves the way for resilient, safety-critical, and scalable control in next-generation DC microgrids.

eess.SY↗

arXiv2025

Fast-Response Variable-Frequency Series-Capacitor Buck VRM Through Integrated Control Approaches

Fast-response voltage regulation is essential for data-center Voltage Regulation Modules (VRMs) powering Artificial Intelligence (AI) workloads, which exhibit both small-amplitude fluctuations and abrupt full-load steps. This paper introduces a control scheme that integrates a linear controller and a nonlinear controller for variable-frequency Series-Capacitor Buck (SCB) converters. First, an accurate small-signal model is derived via a Switching-Synchronized Sampled State-Space (5S) framework, yielding discrete-time transfer functions and root-locus insights for direct digital design. A critical concern for SCB converters is series-capacitor oscillation during heavy load steps if the strict switching sequence is not maintained. To accelerate large-signal transients, a time-optimal control strategy based on Pontryagins Maximum Principle (PMP) relaxes the switching constraints to compute time-optimal switching sequences. A transition logic is then proposed to integrate the high-bandwidth small-signal controller and the large-signal controller. Simulations demonstrate a rapid output voltage recovery under a heavy load step-up, over ten times faster than a linear controller-only design. Preliminary hardware tests indicate a stable rejection to heavy load disturbances with zero steady-state error.

physics.app-ph↗

arXiv2025

Nonlinear Optimal Control of DC Microgrids with Safety and Stability Guarantees

A DC microgrid is a promising alternative to the traditional AC power grid, since it can efficiently integrate distributed and renewable energy resources. However, as an emerging framework, it lacks the rigorous theoretical guarantees of its AC counterpart. In particular, safe stabilization of the DC microgrid has been a non-trivial task in power electronics. To address that, we take a control theoretic perspective in designing the feedback controller with provable guarantees. We present a systematic way to construct Control Lyapunov Functions (CLF) to stabilize the microgrid, and, independently, Control Barrier Functions (CBF) to enforce its safe operation at all times. The safety-critical controller (SCC) proposed in this work integrates the two control objectives, with safety prioritized, into a quadratic program (QP) as linear constraints, which allows for its online deployment using off-the-shelf convex optimization solvers. The SCC is compared against a robust version of the conventional droop control through numerical experiments whose results indicate the SCC outperforms the droop controller in guaranteeing safety and retaining stability at the same time.

eess.SY↗

arXiv2024

Data-Driven Quantification of Battery Degradation Modes via Critical Features from Charging

Battery degradation modes influence the aging behavior of Li-ion batteries, leading to accelerated capacity loss and potential safety issues. Quantifying these aging mechanisms poses challenges for both online and offline diagnostics in charging station applications. Data-driven algorithms have emerged as effective tools for addressing state-of-health issues by learning hard-to-model electrochemical properties from data. This paper presents a data-driven method for quantifying battery degradation modes. Ninety-one statistical features are extracted from the incremental capacity curve derived from 1/3C charging data. These features are then screened based on dispersion, contribution, and correlation. Subsequently, machine learning models, including four baseline algorithms and a feedforward neural network, are used to estimate the degradation modes. Experimental validation indicates that the feedforward neural network outperforms the others, achieving a root mean square error of around 10\% across all three degradation modes (i.e., loss of lithium inventory, loss of active material on the positive electrode, and loss of active material on the negative electrode). The findings in this paper demonstrate the potential of machine learning for diagnosing battery degradation modes in charging station scenarios.

eess.SP↗

arXiv2024

Towards a BMS2 Design Framework: Adaptive Data-driven State-of-health Estimation for Second-Life Batteries with BIBO Stability Guarantees

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).

eess.SY↗

arXiv2024

Taking Second-life Batteries from Exhausted to Empowered using Experiments, Data Analysis, and Health Estimation

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.

cs.LG↗

arXiv2023

A Unified Analytical Method to Quantify Three Types of Fast Frequency Response from Inverter-based Resources

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.

eess.SY↗

arXiv2023

Challenges and Opportunities for Second-life Batteries: A Review of Key Technologies and Economy

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.

eess.SY↗

arXiv2022

Large-Signal Stability Guarantees for Cycle-by-Cycle Controlled DC-DC Converters

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.

eess.SY↗

arXiv2022

Fast-Response Variable Frequency DC-DC Converters Using Switching Cycle Event-Driven Digital Control

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.

eess.SY↗

arXiv2022

Lite-Sparse Hierarchical Partial Power Processing for Second-Use Battery Energy Storage Systems

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.

eess.SY↗

arXiv2022

Overcoming High Frequency Limitations of Current-Mode Control Using a Control Conditioning Approach -- Part I: Modeling and Analysis

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.

eess.SY↗

arXiv2022

Overcoming High Frequency Limitations of Current-Mode Control Using a Control Conditioning Approach -- Part II: Implementation and Hardware

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.

eess.SY↗

arXiv2022

A Note on Comparator-Overdrive-Delay Conditioning for Current-Mode Control

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.

eess.SY↗

arXiv2022

A Note on Low-Pass Filter Conditioning for Current-Mode Control

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.

eess.SY↗

arXiv2022

Comparing Power Processing System Approaches in Second-Use Battery Energy Buffering for Electric Vehicle Charging

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.

eess.SY↗

arXiv2020

Large-Signal Stability Criteria in DC Power Grids with Distributed-Controlled Converters and Constant Power Loads

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.

eess.SY↗