Sensorless current balancing control for interleaved half-bridge submodules in modular multilevel converters

IEEE Transactions on Industrial Electronics

Published On 2023

A new state-observer-based current balancing method for Modular Multilevel Converters with Interleaved half-bridge Sub-Modules (ISM-MMC) is presented in this article. The developed observer allows estimating currents through interleaved half-bridge legs in each submodule of ISM-MMC based only on arm current and submodule's capacitor voltage measurements. Then, the interleaved current balancing control uses the estimated currents to reduce the interleaved currents imbalance caused by upstream control actions. This technique minimizes the number of required current sensors in ISM-MMC, thereby reducing the converter's cost, weight, and volume. Capabilities of the proposed sensorless interleaved currents balancing control have been tested against standard parameter tolerances of the composing passive elements. In addition to that, a novel capacitor voltage balancing strategy for MMCs is …

Journal

IEEE Transactions on Industrial Electronics

Published On

2023

Volume

70

Issue

1

Page

5-16

Authors

Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

Position

Professor at

H-Index(all)

104

H-Index(since 2020)

72

I-10 Index(all)

0

I-10 Index(since 2020)

0

Citation(all)

0

Citation(since 2020)

0

Cited By

0

Research Interests

Power Electronics

Smart Batteries

AI

University Profile Page

Tamás Kerekes

Tamás Kerekes

Aalborg Universitet

Position

H-Index(all)

42

H-Index(since 2020)

31

I-10 Index(all)

0

I-10 Index(since 2020)

0

Citation(all)

0

Citation(since 2020)

0

Cited By

0

Research Interests

power electronics

grid connection

renewable energy

University Profile Page

Gabriele Grandi

Gabriele Grandi

Università degli Studi di Bologna

Position

Full Professor (IT) Senior Member IEEE

H-Index(all)

40

H-Index(since 2020)

24

I-10 Index(all)

0

I-10 Index(since 2020)

0

Citation(all)

0

Citation(since 2020)

0

Cited By

0

Research Interests

Power electronics

Electric circuits

Photovoltaics

University Profile Page

Mattia Ricco

Mattia Ricco

Università degli Studi di Bologna

Position

Assistant Professor -

H-Index(all)

17

H-Index(since 2020)

15

I-10 Index(all)

0

I-10 Index(since 2020)

0

Citation(all)

0

Citation(since 2020)

0

Cited By

0

Research Interests

Power Electronics

EV Chargers

Modular Multilevel Converters

Battery Management Systems

Renewable Energy

University Profile Page

Riccardo Mandrioli, PhD

Riccardo Mandrioli, PhD

Università degli Studi di Bologna

Position

PhD Student and Teaching Assistant

H-Index(all)

11

H-Index(since 2020)

11

I-10 Index(all)

0

I-10 Index(since 2020)

0

Citation(all)

0

Citation(since 2020)

0

Cited By

0

Research Interests

Power Electronics

Power Converters

EV Charger

Transportation Electrification

Modular Multilevel

University Profile Page

Aleksandr Viatkin

Aleksandr Viatkin

Università degli Studi di Bologna

Position

PhD Student IEEE Student Member

H-Index(all)

9

H-Index(since 2020)

9

I-10 Index(all)

0

I-10 Index(since 2020)

0

Citation(all)

0

Citation(since 2020)

0

Cited By

0

Research Interests

power converters

Li-on batteries

grid-forming control

modular multilevel converters

dc protection technologies

University Profile Page

Other Articles from authors

Tamás Kerekes

Tamás Kerekes

Aalborg Universitet

Batteries

Lithium-Ion Supercapacitors and Batteries for Off-Grid PV Applications: Lifetime and Sizing

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Tamás Kerekes

Tamás Kerekes

Aalborg Universitet

Green Energy and Intelligent Transportation

Dual-level design for cost-effective sizing and power management of hybrid energy storage in photovoltaic systems

Integration of hybrid energy storage systems (HESS) into photovoltaic (PV) applications has been a hot topic due to their versatility. However, the proper allocation and power management schemes of HESS are challenges under diverse mission profiles. In this paper, a cost-effectiveness-oriented two-level scheme is proposed as a guideline for the PV-HESS system (i.e., PV, Li-ion battery and supercapacitor), to size the system configuration and extend battery lifespan while considering the power ramp-rate constraint. On the first level, a sizing methodology is proposed to balance the self-sufficiency and the energy throughput between the PV system and the grid to achieve the most cost-effectiveness. On the second level, an improved adaptive ramp-rate control strategy is implemented that dynamically distributes the power between the battery and supercapacitor to reduce the battery cycles. The case study presents …

Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

IEEE Transactions on Industrial Electronics

Health Prediction for Lithium-Ion Batteries Under Unseen Working Conditions

Battery health prediction is significant while challenging for intelligent battery management. This article proposes a general framework for both short-term and long-term predictions of battery health under unseen dynamic loading and temperature conditions using domain-adaptive multitask learning (MTL) with long-term regularization. First, features extracted from partial charging curves are utilized for short-term state of health predictions. Then, the long-term degradation trajectory is directly predicted by recursively using the predicted features within the multitask framework, enhancing the model integrity and lowering the complexity. Then, domain adaptation (DA) is adopted to reduce the discrepancies between different working conditions. Additionally, a long-term regularization is introduced to address the shortcoming that arises when the model is extrapolated recursively for future health predictions. Thus, the short …

Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

IEEE/ASME Transactions on Mechatronics

Online Sensorless Temperature Estimation of Lithium-Ion Batteries Through Electro-Thermal Coupling

Owing to the nonnegligible impacts of temperature on the safety, performance, and lifespan of lithium-ion batteries, it is essential to regulate battery temperature to an optimal range. Temperature monitoring plays a fundamental role in battery thermal management, yet it is still challenged by limited onboard temperature sensors, particularly in large-scale battery applications. As such, developing sensorless temperature estimation is of paramount importance to acquiring the temperature information of each cell in a battery system. This article proposes an estimation approach to obtain the cell temperature by taking advantage of the electrothermal coupling effect of batteries. An electrothermal coupled model, which captures the interactions between the electrical and the thermal dynamics, is established, parameterized, and experimentally validated. A closed-loop observer is then designed based on this coupled model …

Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

Artificial Intelligence-Based State-of-Health Estimation of Lithium-Ion Batteries

The State of Health (SOH) estimation for automotive batteries is currently assessed with different techniques which may involve long testing procedure or require costly hardware to be implemented. This paper aims at contributing to this domain by exploiting the response of a lead-acid battery with respect to a short-term current profile using an Artificial Neural Network (ANN) classifier for SOH estimation. The method is applicable onboard the vehicle and no additional instrumentation is required on the retained vehicle. The design and validation of a SOH method with a short-term current profile using Artificial Intelligence (AI) in lead-acid batteries, which are commonly used in heavy-duty vehicles for cranking and cabin systems, are presented. The paper validates the considered approach with experimental data, which are representative of actual vehicle operations. In detail, the paper describes the retained …

Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

arXiv preprint arXiv:2402.07777

Novel Low-Complexity Model Development for Li-ion Cells Using Online Impedance Measurement

Modeling of Li-ion cells is used in battery management systems (BMS) to determine key states such as state-of-charge (SoC), state-of-health (SoH), etc. Accurate models are also useful in developing a cell-level digital-twin that can be used for protection and diagnostics in the BMS. In this paper, a low-complexity model development is proposed based on the equivalent circuit model (ECM) of the Li-ion cells. The proposed approach uses online impedance measurement at discrete frequencies to derive the ECM that matches closely with the results from the electro-impedance spectroscopy (EIS). The proposed method is suitable to be implemented in a microcontroller with low-computational power, typically used in BMS. Practical design guidelines are proposed to ensure fast and accurate model development. Using the proposed method to enhance the functions of a typical automotive BMS is described. Experimental validation is performed using large prismatic cells and small-capacity cylindrical cells. Root-mean-square error (RMSE) of less than 3\% is observed for a wide variation of operating conditions.

Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

IEEE Transactions on Industrial Informatics

A Battery Digital Twin From Laboratory Data Using Wavelet Analysis and Neural Networks

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Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

IEEE Transactions on Industry Applications

Small-Sample-Learning-Based Lithium-Ion Batteries Health Assessment: An Optimized Ensemble Framework

Machine Learning is widely studied in battery state of health (SOH) estimation due to its advantage in establishing the non-linear mapping between measurements and SOH. However, the requirement of a big dataset and the lack of robustness limit the practical application, especially in small sample learning. To tackle these challenges, an optimal ensemble framework called BaggELM (bagging extreme learning machine) is proposed for battery SOH estimation. Specifically, the required dataset is reduced by optimizing the input voltage and the hyperparameters of the BaggELM algorithm. Moreover, a statistical post-processing method is used to aggregate multiple ELMs, and the final estimate is determined by the maximum probability density value. As a result, the effects of random parameterization of ELM and the training data size on SOH estimation are suppressed, thus improving the robustness and accuracy of …

Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

Intelligent Cell Balancing Control for Lithium-Ion Battery Packs

This study introduces a balancing control strategy that employs an Artificial Neural Network (ANN) to ensure State of Charge (SOC) balance across lithium-ion (Li-ion) battery packs, consistent with the framework of smart battery packs. The model targets a battery pack consisting of cells with diverse characteristics, reflecting real-world heterogeneous conditions. A fundamental aspect of this approach is the ability to bypass individual cells optimally. This key feature stops current flow to and from the cell, allowing it to rest and cool off while avoiding charging or discharging cycles. The implementation of ANN enables adaptive and dynamic management of SOC, which is essential for optimizing performance and extending the lifespan of battery packs. The results demonstrate the effectiveness of the proposed ANN-based balancing strategy in SOC balancing, demonstrating its potential as a critical solution in enhancing battery management systems for electric vehicles.

Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

Grid Impedance Shaping for Grid-Forming Inverters: A Soft Actor-Critic Deep Reinforcement Learning Algorithm

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Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

Electric vehicle battery charging strategy

As a key enabler for transportation electrification and a contributor toward the net-zero carbon future, battery plays a pivotal role in determining the energy management performance of electric vehicles. Technical challenges facing the development of advanced automotive battery charging arise from various contradictory objectives, immeasurable internal states, and hard constraints. This chapter presents a critical introduction to the state-of-the-art charging strategies for the electric vehicle battery and their key enabling technologies. Specifically, battery charging solutions for electric vehicles are first classified and discussed. Then, the battery models on which these solutions rest are stated, the related charging frameworks are summarized, and the advantages and drawbacks of the adopted technologies are discussed. Suggestions for overcoming the limitations of the discussed charging strategies are proposed …

Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

Thermal state monitoring of lithium-ion batteries: Progress, challenges, and opportunities

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Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

Reliability Engineering & System Safety

Predictive health assessment for lithium-ion batteries with probabilistic degradation prediction and accelerating aging detection

Predictive health assessment is of vital importance for smarter battery management to ensure optimal and safe operations and thus make the most use of battery life. This paper proposes a general framework for battery aging prognostics in order to provide the predictions of battery knee, lifetime, state of health degradation, and aging rate variations, as well as the assessment of battery health. Early information is used to predict knee slope and other life-related information via deep multi-task learning, where the convolutional-long-short-term memory-bayesian neural network is proposed. The structure is also used for online state of health and degradation rate predictions for the detection of accelerating aging. The two probabilistic predicted boundaries identify the accelerating aging regions for battery health assessment. To avoid wrong and premature alarms, the empirical model is used for data preprocessing and …

Tamás Kerekes

Tamás Kerekes

Aalborg Universitet

Solar Energy

An adaptive power smoothing approach based on artificial potential field for PV plant with hybrid energy storage system

The increasing quantity of PV installation has brought great challenges to the grid owing to power fluctuations. Hybrid energy storage systems have been an effective solution to smooth out PV output power variations. In order to reduce the required capacity and extend the lifetime of the hybrid energy storage system, a two-stage self-adaptive smoothing approach based on the artificial potential field is proposed to decompose and allocate power among the grid, battery, and supercapacitor dynamically. In the ramp rate control stage, an unsymmetric artificial potential field method is used to regulate the cutoff frequency of a low-pass filter, so as to limit the PV power ramp rate within the prescribed range and allocate the power between the grid and the hybrid energy storage system. In the HESS power distribution stage, a symmetric artificial potential field is adopted to distribute power between the battery and …

Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

Fractional-order control techniques for renewable energy and energy-storage-integrated power systems: A review

The worldwide energy revolution has accelerated the utilization of demand-side manageable energy systems such as wind turbines, photovoltaic panels, electric vehicles, and energy storage systems in order to deal with the growing energy crisis and greenhouse emissions. The control system of renewable energy units and energy storage systems has a high effect on their performance and absolutely on the efficiency of the total power network. Classical controllers are based on integer-order differentiation and integration, while the fractional-order controller has tremendous potential to change the order for better modeling and controlling the system. This paper presents a comprehensive review of the energy system of renewable energy units and energy storage devices. Various papers are evaluated, and their methods and results are presented. Moreover, the mathematical fundamentals of the fractional-order method are mentioned, and the various studies are categorized based on different parameters. Various definitions for fractional-order calculus are also explained using their mathematical formula. Different studies and numerical evaluations present appropriate efficiency and accuracy of the fractional-order techniques for estimating, controlling, and improving the performance of energy systems in various operational conditions so that the average error of the fractional-order methods is considerably lower than other ones.

Tamás Kerekes

Tamás Kerekes

Aalborg Universitet

A Control-Oriented Voltage Tracking Design for Grid-Forming Based Modular Multilevel Converter

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Gabriele Grandi

Gabriele Grandi

Università degli Studi di Bologna

Design considerations on modular WPT charging systems for drones in civil applications

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Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

IEEE Transactions on Vehicular Technology

Battery states monitoring for electric vehicles based on transferred multi-task learning

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Tamás Kerekes

Tamás Kerekes

Aalborg Universitet

Energies

Robust PLL-Based Grid Synchronization and Frequency Monitoring

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Remus Teodorescu

Remus Teodorescu

Aalborg Universitet

Battery aging behavior evaluation under variable and constant temperatures with real loading profiles

Studying and analyzing battery aging behavior is crucial in battery health prognostic and management. This paper conducts novel and comprehensive experiments to evaluate battery aging under variable external stresses, including different dynamic load profiles and variable environmental temperatures. Respond analysis in the time and frequency domain is performed to account for the different aging rates under different current loadings, where the statistic calculation and fast Fourier transform are used for the analysis. The empirical model is used to fit the fade curve for the comparisons between constant and variable temperatures. The capacity decrease and internal resistance increase are extracted to evaluate capacity and power fade, respectively. The experimental results show that the urban dynamic operating conditions help to prolong the service life compared to the constant current aging case. In contrast …

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Article Details
Zhiqiang Miao(缪志强)

Zhiqiang Miao(缪志强)

Hunan University

IEEE Transactions on Industrial Electronics

Dual Model Predictive Control of Multiple Quadrotors With Formation Maintenance and Collision Avoidance

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Yanjie Chen (陈彦杰)

Fuzhou University

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Nanjing University of Science and Technology

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Harbin Institute of Technology

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Kansas State University

IEEE Transactions on Industrial Electronics

Grid-Forming Inverters in a Microgrid: Maintaining Power During an Outage and Restoring Connection to the Utility Grid Without Communication

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University of Strathclyde

IEEE Transactions on Industrial Electronics

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Zahra Nasiri-Gheidari

Sharif University of Technology

IEEE Transactions on Industrial Electronics

Proposal of a Wound-Rotor PCB-Resolver

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Aalborg Universitet

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Southeast University

IEEE Transactions on Industrial Electronics

A general control method for half-centralized open winding permanent-magnet motor drive system

In this article, a general control method based on duty ratio selection for half-centralized open winding primary permanent-magnet linear motor drive system is proposed. The proposed control method is designed from the perspective of single-phase subsystem. The novelty of this article is the voltage process and modulation, which can realize the expansion from two movers to multimovers. The design of voltage process and modulation contains voltage preprocessor, saturation limiter, and duty ratio distributor. In the voltage preprocessor, phase voltages are transferred to phase modulation index. The saturation limiter deals with excessive phase modulation indexes based on the independent overmodulation principle. The duty ratio distributor distributes the voltage demand into inverters by the common-leg-based distribution principle. Compared to existing methods, the proposed control method can realize the …

Josep Pou

Josep Pou

Nanyang Technological University

IEEE Transactions on Industrial Electronics

Constant Current Precharging Algorithm for Solid State Power Controllers

Semiconductor-based solid-state power controllers (SSPCs) are a promising solution for dc system protection. During the connection of capacitive loads there is an inrush current because of zero initial energy in the capacitor, which can cause damage to the system. One of the main challenges of SSPCs is to suppress the current and voltage overshoot during precharging. In most of the precharging methods, additional circuitry is required, which adds weight, size, and complexity to the system. In this article, a constant current precharging algorithm is proposed. The main semiconductor device is utilized for precharging instead of adding an auxiliary circuit, thus reducing the required number of components. In addition, the proposed algorithm has a higher adaptability to the change of system parameters. Moreover, it is easily implementable to a wide range of semiconductor devices. Analytical evaluations are …

Wei Hua (花为)

Wei Hua (花为)

Southeast University

IEEE Transactions on Industrial Electronics

Robust Diagnosis of Partial Demagnetization Fault in PMSMs Using Radial Air-Gap Flux Density Under Complex Working Conditions

Partial demagnetization fault (PDF) is a common problem for permanent magnet synchronous motor (PMSM). The PMSM usually operates under complex working conditions (dynamic speed and various load), leading to the difficulty in robust PDF diagnosis. Hence, how to reliably and accurately diagnose PDF under complex working conditions has become a key issue in ensuring its safe operation. To address this issue, a robust PDF diagnosis method for PMSM is proposed based on radial air-gap flux density in this article. First, the d -axis magnetic network model of PMSM is established to extract the fault feature from the radial air-gap flux density. Then, by subtracting the offline-calculated radial air-gap flux density of stator current excitation from the online measured value, the open-circuit radial air-gap flux density can be calculated. Next, the equiangular interval resampling method is used to obtain the open …

Zhongbao Wei(魏中宝)

Zhongbao Wei(魏中宝)

Beijing Institute of Technology

IEEE Transactions on Industrial Electronics

Cathodic Supply Optimization of PEMFC System Under Variable Altitude

The efficiency of the proton exchange membrane fuel cell (PEMFC) system drops remarkably with the changed ambient pressure and temperature under variable altitudes. To enhance the adaptability of PEMFC, this article proposes a hierarchical optimal control strategy (HOCS) that guarantees the efficient operation of the PEMFC system during changes in altitude. In particular, the sparrow search algorithm (SSA) is exploited to optimize the air supply strategy under different operating conditions. To support the HOCS, a variable altitude model of PEMFC is established, which integrates the environmental impacts on components. A sliding mode controller (SMC) is employed to achieve precise and fast control of the air supply system across various situations. Comparative results validate the superiority of the proposed method in terms of the efficiency of the air compressor and the net power output. In a typical driving …

Tianliang Li

Tianliang Li

National University of Singapore

IEEE Transactions on Industrial Electronics

Modular and Fault-Tolerant Three-Axial FBG-Based Force Sensing for Transoral Surgical Robots

Transoral robotic surgery (TROS) has met a significant challenge to precise control of surgical instruments and depress the injury risks without force feedback. Therefore, we develop a modular high-precision three-axial fiber Bragg grating (FBG) force sensor with nonlinear decoupling, fault tolerance, and temperature compensation (TC) for seamless integration into transoral robots. The sensor comprises a one-body elastomer housing four optical fibers engraved with FBG each, arranged at a constant interval of 90° along the circumference to enhance three-axial force perception through redundancy. A novel dung Beetle optimization extreme learning machine (DBO-ELM) algorithm is proposed to tackle nonlinear coupling, FBG fracture, and temperature interference challenges leading to excellent performances of accurate and reliable measurement. The maximum full-scale error is less than 4% in each dimension …

Chunhua Yang

Chunhua Yang

Central South University

IEEE Transactions on Industrial Electronics

Multimodel Self-Learning Predictive Control Method With Industrial Application

In industrial sites, system operation conditions fluctuate due to changes in raw material and equipment status, making it critical to identify the operation conditions and obtain appropriate controllers accurately. Additionally, even for a specific operation condition, fixed control strategies may result in mismatches due to varying operational stages. To address the accurate control of industrial processes across multiple operation conditions, this article proposes a multimodel self-learning predictive control (MSLPC) method to simultaneously improve the accuracy of offline condition partition and online control performance. Specifically, in the offline stage, for complex and multidimensional industrial data, condition indicators are selected based on expert systems and data analytics, and a “presetting precise-fusion” two-stage operation condition learning (TSOCL) algorithm is proposed to accurately identify the operation …

Choon Ki Ahn

Choon Ki Ahn

Korea University

IEEE Transactions on Industrial Electronics

Model-Free Filter-Based Single-Loop Output-Feedback System Design for PMSMs With Critically Damped Performance

This article designs a filter-based output-feedback system to regulate the speed of permanent magnet synchronous motors (PMSMs), which structures a simple single-loop form compensated by feed-forward terms. The proposed controller design framework considerably reduces the dependence level of the PMSM model by requiring partial nominal parameter values for control law and removing the model structure and whole parameter information for the filter. The main advantages consist of two parts. First, the proposed observer employs the second-order pole-zero cancelation (PZC) technique to continuously extract the speed and acceleration from noisy position measurements by the rotary encoder, independent from the PMSM model. Second, the PZC filter-based proportional–integral control forms a single-loop feedback system including the active damping injection and disturbance observer, which assigns …

Sang-Won Lee

Sang-Won Lee

Kongju National University

IEEE Transactions on Industrial Electronics

Quasi-Resonant Fly-Buck Converter With Active Switching for Improved Output Voltage Boosting and Regulation

This article proposes a quasi-resonant fly-buck converter using an active switching operation at the isolated load side. The proposed circuit overcomes the cross-regulation and low voltage gain problems of the conventional fly-buck converter with the simple quasi-resonance operation between the inherent leakage inductance of a transformer and an auxiliary capacitor at the isolated secondary side. The converter implements the high step-up operation using an auxiliary switch; therefore, the reduced winding ratio of the transformer improves the power density of the circuit. In addition, this circuit implements the soft switching at all active components, and does not suffer from the reverse recovery problem at a diode. A 20 W prototype having an input voltage of 12 V was built to prove the theoretical analyses, and it regulated 5 V for 10 W and 15 V for 10 W at the primary nonisolated and secondary isolated load sides …

Xiaoshan Bai

Xiaoshan Bai

Technische Universiteit Delft

IEEE Transactions on Industrial Electronics

Efficient Performance Impact Algorithms for Multirobot Task Assignment With Deadlines

This article investigates the multirobot task assignment problem with deadlines, where a group of distributed heterogeneous robots needs to collaborate effectively to first maximize the number of successful search and rescue missions and then minimize the robots' total service time. First, a distributed performance impact algorithm is designed to obtain the initial assignment solution, where each robot can compute its assignment solution independently. Subsequently, based on different local search strategies, a disturbance mechanism and two improvement strategies, namely, first, global task inclusion first and decoupled 1-opt second phase and, second, global task inclusion first and coupled 1-opt second phase, are proposed to disrupt and refine the initial solution. The integration of the distributed performance impact algorithm with the two refinement strategies leads to a decoupled performance impact algorithm …

zhiliang zhang

zhiliang zhang

Nanjing University of Aeronautics and Astronautics

IEEE Transactions on Industrial Electronics

Digital Synchronous Rectifier Control Using Extended Harmonics Impedance Model for High-Frequency GaN-Based LLC Converters

Conventional LLC synchronous rectifier (SR) schemes use detection circuits to sense the signals of voltage or current. But it typically operates below 500 kHz, which is unsuitable for high-frequency applications as it may lose large SR duty cycle caused by high dv/dt and GaN devices usage. To address the serious challenge, a digital SR control using extended harmonics impedance model is proposed for GaN LLC converters. By building the impedance model, the SR on-time is calculated accurately in the microcontroller. It not only minimizes the on-time of SR body diode with high precision, but also owns high immunity. A 650-kHz 1.5-kW GaN LLC converter was built. With the output of 28 V/53.5 A, the efficiency is as high as 98.1% at 1.5 kW by using the proposed SR. The power density is also up to 524 W/in 3 . Compared to the conventional SR, the efficiency improves 1.6% at full load.