Krishna R. Pattipati
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View article: Two-Stage Least Squares for Equivalent-Circuit Model Parameter Estimation of Li-ion Batteries Using Pulse-Relaxation Excitation
Two-Stage Least Squares for Equivalent-Circuit Model Parameter Estimation of Li-ion Batteries Using Pulse-Relaxation Excitation Open
View article: Excitation Signal Design for Fast Electrochemical Impedance Spectroscopy in Battery Testing
Excitation Signal Design for Fast Electrochemical Impedance Spectroscopy in Battery Testing Open
Electrochemical impedance spectroscopy (EIS) is a widely used technique for analyzing battery dynamics over a broad frequency spectrum. Conventional state-of-the-art EIS methods involve applying a sequence of sinusoidal excitation signals,…
View article: Piecewise Linear Approximation of Battery Open-Circuit Voltage Characteristics Using Dynamic Programming
Piecewise Linear Approximation of Battery Open-Circuit Voltage Characteristics Using Dynamic Programming Open
View article: Excitation Signal Design for Fast Electrochemical Impedance Spectroscopy in Battery Testing
Excitation Signal Design for Fast Electrochemical Impedance Spectroscopy in Battery Testing Open
Electrochemical impedance spectroscopy (EIS) is a widely used technique for analyzing battery dynamics over a broad frequency spectrum. Conventional state-of-the-art EIS methods involve applying a sequence of sinusoidal excitation signals,…
View article: Probability propagation for path planning in unknown environments
Probability propagation for path planning in unknown environments Open
View article: An Improved Approach to Estimate the Internal Resistance of a Battery During the HPPC Test
An Improved Approach to Estimate the Internal Resistance of a Battery During the HPPC Test Open
This paper considers the problem of resistance estimation in electronic systems including battery management systems (BMS) and battery chargers. In typical applications, the battery resistance is obtained through an approximate method comp…
View article: Improved Estimation of Open Circuit Voltage and Internal Resistance of a Battery Using Novel Voltage Observation Model
Improved Estimation of Open Circuit Voltage and Internal Resistance of a Battery Using Novel Voltage Observation Model Open
View article: Learning Composite Representations for Tool Diagnostics in Industrial Settings
Learning Composite Representations for Tool Diagnostics in Industrial Settings Open
View article: A Study on the Effect of Temperature on Low-Rate Open-Circuit Voltage Models of Lithium-Ion Batteries
A Study on the Effect of Temperature on Low-Rate Open-Circuit Voltage Models of Lithium-Ion Batteries Open
View article: Image-based Cutting Tool Health Diagnosis in Multi-machine Settings
Image-based Cutting Tool Health Diagnosis in Multi-machine Settings Open
View article: Fault Diagnosis and Prognosis With Inferential Sensors: A Hybrid Approach Integrating Symbolic Regression and Information Theory
Fault Diagnosis and Prognosis With Inferential Sensors: A Hybrid Approach Integrating Symbolic Regression and Information Theory Open
We propose a fault diagnosis approach that integrates symbolic regression and information theory to optimize inferential sensors, which, along with traditional detection techniques and hard sensors, contribute to a comprehensive fault dete…
View article: Piecewise Linear Approximation of Battery Open-Circuit Voltage Characteristics Using Dynamic Programming
Piecewise Linear Approximation of Battery Open-Circuit Voltage Characteristics Using Dynamic Programming Open
View article: OPMOS: Ordered Parallel Algorithm for Multi-Objective Shortest-Paths
OPMOS: Ordered Parallel Algorithm for Multi-Objective Shortest-Paths Open
The Multi-Objective Shortest-Path (MOS) problem finds a set of Pareto-optimal solutions from a start node to a destination node in a multi-attribute graph. The literature explores multi-objective A*-style algorithmic approaches to solving …
View article: Real-time State of Power Estimation of a Lithium-Ion Battery Using Robust OCV and Internal Resistance Estimates
Real-time State of Power Estimation of a Lithium-Ion Battery Using Robust OCV and Internal Resistance Estimates Open
The state of power (SOP) refers to the maximum available power from a battery. The SOP is a function of the open circuit voltage and internal resistance of the battery, both of which change with the state of charge (SOC). As such, the SOP …
View article: Real-time State of Power Estimation of a Lithium-Ion Battery Using Robust OCV and Internal Resistance Estimates
Real-time State of Power Estimation of a Lithium-Ion Battery Using Robust OCV and Internal Resistance Estimates Open
The state of power (SOP) refers to the maximum available power from a battery. The SOP is a function of the open circuit voltage and internal resistance of the battery, both of which change with the state of charge (SOC). As such, the SOP …
View article: Tool wear and remaining useful life estimation in precision machining using interacting multiple model
Tool wear and remaining useful life estimation in precision machining using interacting multiple model Open
View article: Estimating Remaining Useful Life of Cutting Tools in Machining Using an Extended Kalman Filter
Estimating Remaining Useful Life of Cutting Tools in Machining Using an Extended Kalman Filter Open
View article: Subseasonal to Seasonal (S2S) Prediction Algorithms using Hybrid Machine Learning Techniques
Subseasonal to Seasonal (S2S) Prediction Algorithms using Hybrid Machine Learning Techniques Open
< S2S dataset.zip > 1.ECMWF observations/hindcast realizations hindcast-like-observations_2000-2019_biweekly_deterministic.zarr forecast-like-observations_2020_biweekly_deterministic.zarr ecmwf_hindcast-input_2000-2019_biweekly_determinist…
View article: Subseasonal to Seasonal (S2S) Prediction Algorithms using Hybrid Machine Learning Techniques
Subseasonal to Seasonal (S2S) Prediction Algorithms using Hybrid Machine Learning Techniques Open
1.ECMWF observations/hindcast realizations hindcast-like-observations_2000-2019_biweekly_deterministic.zarr forecast-like-observations_2020_biweekly_deterministic.zarr ecmwf_hindcast-input_2000-2019_biweekly_deterministic.zarr ecmwf_foreca…
View article: Subseasonal to Seasonal (S2S) Prediction Algorithms using Hybrid Machine Learning Techniques
Subseasonal to Seasonal (S2S) Prediction Algorithms using Hybrid Machine Learning Techniques Open
< S2S dataset.zip > 1.ECMWF observations/hindcast realizations hindcast-like-observations_2000-2019_biweekly_deterministic.zarr forecast-like-observations_2020_biweekly_deterministic.zarr ecmwf_hindcast-input_2000-2019_biweekly_determinist…
View article: Computational Algorithms for Acoustic Signals Direction of Arrival and Sound Speed Estimation
Computational Algorithms for Acoustic Signals Direction of Arrival and Sound Speed Estimation Open
This paper develops computationally efficient algorithms for the analysis of acoustic data to localize a target through improved angle of arrival estimation. The passive target localization problem has a wide range of applications in wirel…
View article: Minimum Time Sailing Boat Path Algorithm
Minimum Time Sailing Boat Path Algorithm Open
An iterative procedure to solve the nonlinear problem of fastest-path sailing vessel routing in an environment with variable winds and currents is proposed. In the routing of a sailing vessel, the primary control variable is the pointing (…
View article: Sequential Mini-Batch Noise Covariance Estimator
Sequential Mini-Batch Noise Covariance Estimator Open
Noise covariance estimation in an adaptive Kalman filter is a problem of significant practical interest in a wide array of industrial applications. Reliable algorithms for their estimation are scarce, and the necessary and sufficient condi…
View article: Physics-Informed Gaussian Mixture Model for Tool Condition Monitoring
Physics-Informed Gaussian Mixture Model for Tool Condition Monitoring Open
View article: Robust Approach to Battery Equivalent-Circuit-Model Parameter Extraction Using Electrochemical Impedance Spectroscopy
Robust Approach to Battery Equivalent-Circuit-Model Parameter Extraction Using Electrochemical Impedance Spectroscopy Open
Electrochemical impedance spectroscopy (EIS) is a well-established method of battery analysis, where the response of a battery to either a voltage or current excitation signal spanning a wide frequency spectrum is measured and analyzed. St…
View article: Tabular Open Circuit Voltage Modelling of Li-Ion Batteries for Robust SOC Estimation
Tabular Open Circuit Voltage Modelling of Li-Ion Batteries for Robust SOC Estimation Open
Battery management systems depend on open circuit voltage (OCV) characterization for state of charge (SOC) estimation in real time. The traditional approach to OCV-SOC characterization involves collecting OCV-SOC data from sample battery c…
View article: Optimizing Current Profiles for Efficient Online Estimation of Battery Equivalent Circuit Model Parameters Based on Cramer–Rao Lower Bound
Optimizing Current Profiles for Efficient Online Estimation of Battery Equivalent Circuit Model Parameters Based on Cramer–Rao Lower Bound Open
Battery management systems (BMS) are important for ensuring the safety, efficiency and reliability of a battery pack. Estimating the internal equivalent circuit model (ECM) parameters of a battery, such as the internal open circuit voltage…
View article: Open-Circuit Voltage Models for Battery Management Systems: A Review
Open-Circuit Voltage Models for Battery Management Systems: A Review Open
A battery management system (BMS) plays a crucial role to ensure the safety, efficiency, and reliability of a rechargeable Li-ion battery pack. State of charge (SOC) estimation is an important operation within a BMS. Estimated SOC is requi…
View article: A Single-pass Noise Covariance Estimation Algorithm in Multiple-model Adaptive Kalman Filtering for Non-stationary Systems
A Single-pass Noise Covariance Estimation Algorithm in Multiple-model Adaptive Kalman Filtering for Non-stationary Systems Open
Estimation of unknown noise covariances in a Kalman filter is a problem of significant practical interest in a wide array of applications. This paper presents a single-pass stochastic gradient descent (SGD) algorithm for noise covariance e…
View article: Sensor selection and tool wear prediction with data‐driven models for precision machining
Sensor selection and tool wear prediction with data‐driven models for precision machining Open
Estimation of tool wear in precision machining is vital in the traditional subtractive machining industry to reduce processing cost, improve manufacturing efficiency and product quality. In this vein, fusion of time and frequency‐domain fe…