A5049358578- Advanced Battery Technologies Research
- Advancements in Battery Materials
- Fault Detection and Control Systems
- Control Systems and Identification
- Target Tracking and Data Fusion in Sensor Networks
- Advanced Battery Materials and Technologies
- Distributed Control Multi-Agent Systems
- Stability and Control of Uncertain Systems
- Advanced Control Systems Optimization
- Adaptive Control of Nonlinear Systems
- Electric Vehicles and Infrastructure
- Advanced DC-DC Converters
- Neural Networks Stability and Synchronization
- Microgrid Control and Optimization
- Advanced battery technologies research
- Reservoir Engineering and Simulation Methods
- Structural Health Monitoring Techniques
- Fuel Cells and Related Materials
- Energy Harvesting in Wireless Networks
- Model Reduction and Neural Networks
- Iterative Learning Control Systems
- Neural Networks and Applications
- Gaussian Processes and Bayesian Inference
- Supercapacitor Materials and Fabrication
- Smart Grid Security and Resilience
University of Kansas
2015-2024
University of California, Berkeley
2021
University of Victoria
2017
University of California, San Diego
2010-2015
Mitsubishi Electric (United States)
2014
Mitsubishi Group (Japan)
2013
University of Saskatchewan
2008-2009
This paper surveys the recent advances in marine mechatronic systems from a control perspective. The survey is by no means exhaustive, but introduces some notable results area. New developments terms of system designs for surface vessels, underwater robotic vehicles, profiling floats, gliders, wave energy converters, and offshore wind turbines are briefly reviewed. In addition, few avenues future research identified.
This article presents an up-to-date tutorial review of nonlinear Bayesian estimation. State estimation for systems has been a challenge encountered in wide range engineering fields, attracting decades research effort. To date, one the most promising and popular approaches is to view address problem from probabilistic perspective, which enables unknown state variables by tracking their distribution or statistics (e.g., mean covariance) conditioned on system's measurement data. offers...
We consider the problem of parameter estimation and output for systems in a transmission control protocol (TCP) based network environment. As result networked-induced time delays packet loss, input data are inevitably subject to randomly missing data. Based on available incomplete data, we first model as two separate Bernoulli processes characterised by probabilities then estimator is designed, finally develop recursive algorithm modifying Kalman filter-based algorithm. Under stochastic...
A battery pack can see energy imbalance among its cells resulting from cell-to-cell variation in capacity, internal resistance, and other parameters. Its successful safe operation thus necessitates dynamic equalizing to adjust each cell's state-of-charge the same level. The cell system for a serially connected is modeled as multiagent here. consensus-based algorithm proposed with convergence proved through theoretical analysis. Following this development, an interesting important problem...
Cyber-physical systems (CPSs) have attracted increasing attention in recent years due to their promise for substantial and long-term benefits society, economy, environment, citizens. In addition, the rapid advances computing, communication, storage technologies resulted a revolution information communication technology domain domination industry context. The utilization of CPSs industrial settings has led cyber-physical (ICPSs), which, conjunction with information-driven interactions,...
Advanced battery management is as important for lithium-ion systems the brain human body. Its performance based on use of fast and accurate models. However, mainstream equivalent circuit models electrochemical have yet to meet this need well, due their struggle with either predictive accuracy or computational complexity. This problem has acquired urgency some emerging applications running across broad current ranges, e.g., electric vertical take-off landing aircraft, can hardly find usable...
Abstract This paper investigates the problem of adaptive control for networked systems with unknown model parameters and randomly missing outputs. In particular, a system autoregressive exogenous input placed in network environment, output feature is modeled as Bernoulli process. Then, an estimator designed to online estimate measurements, further Kalman filter‐based method proposed parameter estimation. Based on estimated available output, parameters, make track desired signal. Convergence...
This paper considers the state of charge (SoC) and parameter estimation lithium-ion batteries. Different from various prior arts, where is based on local linearization a nonlinear battery model, geometric observer approach followed to design adaptive observers for SoC models. A major advantage proposed possibility establish exponential stability resultant error dynamics estimation. The are shown be robust with respect unmodeled process uncertainties. Analysis also shows tradeoff between...
With high energy/power density, flexible and lightweight design, low self-discharge rates long cycle life, lithium-ion (Li <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> ) batteries have experienced a surging growth since being commercialized in the early 1990s [1]. They are dominant today consumer electronics sector. Due to continually declining manufacturing costs, they also rapidly penetrating sectors such as power grid, renewable...
This paper studies control-theory-enabled intelligent charging management for battery systems in electric vehicles (EVs). Charging is crucial the performance and life as well a contributory factor to user's confidence or anxiety about EVs. For existing practices methods, many run with lack of health awareness during charging, none includes user needs into loop. To remedy such deficiencies, we propose perform that, first time, allows specify objectives accomplish them through dynamic control,...
In this paper, we consider the optimal coordination problem for distributed energy resources (DERs), including generators and storages. We first propose an algorithm based on push-sum gradient method to solve DER in a manner. proposed algorithm, each only maintains set of variables updates them through information exchange with few neighboring DERs over time-varying directed communication network. show that appropriately chosen diminishing step sizes solves if network is uniformly jointly...
Successful operation of a battery pack necessitates an effective charging management. This study presents systematic investigation that blends control design with implementation for charging. First, it develops multimodule charger serially connected pack, which allows each cell to be charged independently by modified isolated buck converter. Then, the development two-layer hierarchical approach run on this charger. The top-layer schedules optimal currents through multiobjective optimization...
Abstract This work is devoted to solving simultaneous input and state estimation (SISE) problem for discrete‐time linear systems. Our aim develop stable SISE algorithms. By applying the minimum variance unbiased technique, we derive two algorithms in presence or absence of direct feedthrough, respectively. Riccati‐like equations are formulated presented analyze stability conditions proposed Simulation examples provided further illustrate effectiveness support theoretical findings. Copyright...
This article proposes a new equivalent circuit model for rechargeable batteries by modifying double-capacitor in the literature. It is known that original can address rate capacity effect and energy recovery inherent to better than other models. However, it purely linear includes no representation of battery's nonlinear phenomena. Hence, this transforms introducing nonlinear-mapping-based voltage source serial RC circuit. The modification justified an analogy with single-particle model. Two...
The rapidly growing use of lithium-ion batteries across various industries highlights the pressing issue optimal charging control, as plays a crucial role in health, safety and life batteries. literature increasingly adopts model predictive control (MPC) to address this issue, taking advantage its capability performing optimization under constraints. However, computationally complex online constrained intrinsic MPC often hinders real-time implementation. This paper is thus proposed develop...
Outliers can be caused by sensor errors, model uncertainties, changes in the ambient environment, data loss, or malicious cyberattacks to contaminate measurement process of many nonlinear dynamic systems. When extended Kalman filter (EKF) is applied such systems for state estimation, outliers seriously reduce estimation accuracy. This brief proposes an innovation saturation mechanism make EKF robust against outliers. applies a function that leverages correct estimation. As such, when occur,...
This article focuses on state-of-charge (SoC) estimation for a lithium-ion battery modeled using recently developed nonlinear double-capacitor representation that has been shown to be highly accurate. The measurement equation of the model two functions, one them being significant hysteresis in voltage as function SoC. term is physically intuitive modified Preisach consisting series hysterons which get switched <sc xmlns:mml="http://www.w3.org/1998/Math/MathML"...
Stochastic differential equations (SDEs) are mathematical models that widely used to describe complex processes or phenomena perturbed by random noise from different sources. The identification of SDEs governing a system is often challenge because the inherent strong stochasticity data and complexity system's dynamics. practical utility existing parametric approaches for identifying usually limited insufficient resources. This study presents novel framework leveraging sparse Bayesian...