Publications

Initiatives to decarbonize contemporary power systems will lead to power systems dominated by inverter-based resources (IBR). These IBRs are broadly classified into grid-following (GFL) and grid-forming (GFM) inverter control regimes. In this paper, a small-signal state-space model is formulated for a 100% IBR-dominated power system. This formulation is then used to perform stability analysis on the IEEE 9-bus system. The analysis thoroughly investigates the impacts of varying GFM inverter penetration on system stability. The paper also discusses the system behavior in the wake of varying shares of different GFL inverter control schemes. The cause of instability is ascertained by investigating the participation factor of each component. Moreover, the paper examines the effects of phase-locked loop (PLL) and power synchronization loop (PSL) parameters on determining the minimum GFM penetration necessary for ensuring stable system operation. It has been found that the inverter type with the highest capacity is not always the biggest contributor to instability. Also, increasing the proportional coefficient and decreasing the integral coefficient of the PLL of GFL inverters allow the system to be operated under lower GFM penetration. Similarly, increasing the moment of inertia or damping coefficient of the GFM inverter’s power synchronization loop has a similar effect. The conclusions and the underlying theoretical analysis are verified by time-domain simulations of electromagnetic transient (EMT) models in Matlab/Simulink.

Grid-forming converters (GFMCs), which provide superior grid formulation and supportive services, have been identified as the enabler of more-electronics power systems. Control of GFMCs mainly comprises outer-power and inner-voltage loops. Although existing literature assumes that the two loops can be independently analyzed and designed, we reveal that the converter may be unstable even with two individually stabilized control loops, thereby implying their strong coupling effect. To realize the decoupling design of power and voltage control loops, we propose a robust singular perturbation method, which comprises a marriage of robust control and singular perturbation theory. Specifically, we construct the converter model as an interconnection of slow and fast subsystems, and derive two quantitative criteria regarding system stability and performance, respectively. Through the proposed method, we successfully quantify the coupling effects between the two loops at each frequency point, enabling the identification of the maximum coupling and the critical coupling frequency. Accordingly, we provide insightful guidelines for simplified controller design. The correctness of the theoretical analysis and the effectiveness of the proposed decoupling method are validated by simulation and experimental results.

Multilevel converters are widely used in various industrial applications. One of the critical challenges in these systems is the suppression of common-mode voltage (CMV). Due to the intuitive nature of the space vector diagram, space vector PWM (SVPWM) can effectively regulate CMV. However, as the number of voltage levels in multilevel converters increases, the complexity of the SVPWM method also grows. Existing simplified SVPWM techniques, which are helpful, have not been fully successful in suppressing the CMV. To address the above issues, this paper proposes a generic SVPWM (GSVPWM) method. Unlike conventional approaches, the GSVPWM is based on the natural abc coordinate system, eliminating the need for coordinate transformations. In addition to effectively suppressing both the magnitude and frequency of the CMV, the GSVPWM further reduces the dv/dt values of the CMV by subdividing the equilateral triangular sectors into obtuse triangular sectors. The proposed method operates in real-time, without requiring look-up tables or complex calculations. It is easy to implement across different multilevel converters. Simulations and the experiments are conducted in a five-level converter to verify the effectiveness of the proposed GSVPWM.

This IEC White Paper establishes the critical role that power semiconductors play in transitioning to an energy wise society. It takes an in-depth look at expected trends and opportunities, as well as the challenges surrounding the power semiconductors industry. Among the significant challenges mentioned is the need for change in industry practices when transitioning from linear to circular economies and the shortage of skilled personnel required for power semiconductor development. The white paper also stresses the need for strategic actions at the policy-making level to address these concerns and calls for stronger government commitment, policies and funding to advance power semiconductor technologies and integration. It further highlights the pivotal role of standards in removing technical risks, increasing product quality and enabling faster market acceptance. Besides noting benefits of existing standards in accelerating market growth, the paper also identifies the current standardization gaps. <br/>The white paper emphasizes the importance of ensuring a robust supply chain for power semiconductors to prevent supply-chain disruptions like those seen during the COVID-19 pandemic, which can have widespread economic impacts.<br/>The white paper highlights the importance of inspiring young professionals to take an interest in power semiconductors and power electronics, highlighting the potential to make a positive impact on the world through these technologies.<br/>The white paper concludes with recommendations for policymakers, regulators, industry and other IEC stakeholders for collaborative structures and accelerating the development and adoption of standards.

Synchronization stability assessment of grid-forming (GFM) converters is essential during and after large disturbances in the external grid, where the active power control (APC) loop is perceived as the key concern since it is employed to generate the voltage phase angle. However, the impacts of the internal voltage amplitude dynamics and current saturation, determined by the reactive power control (RPC) loop and current limiter, are often neglected. This paper considers dynamic interactions between internal voltage magnitude and phase angle to derives an improved power-angle curve of the circular current-limited GFM converter, which facilitates more accurate identification of the critical angle margin for evaluating the synchronization stability after phase jumps. Furthermore, the impact of the RPC coefficient is quantified to provide parameter design recommendations for enhancing the post-phase jump synchronization stability. The analytical results are validated by simulations and experimental tests.

Predictive control is widely used in power electronic converters for its simplicity, clear objectives, and ease of constraint implementation. However, its computational demand increases with the pursuit of higher accuracy and performance, potentially compromising real-time operation due to the fast dynamics of converters. To address this challenge, this paper applies a novel differentiable predictive control method for real-time control of power converters. By integrating predictive control principles into the neural network framework, the method transforms the network into an automated predictive control solver through gradient descent optimization offline. Unlike supervised learning-based neural networks, this approach eliminates the need for pre-labeled data or extensive training, offering an efficient solution for achieving precise and timely control. This new method enhances the implementation feasibility of predictive control in real-time applications, addressing computational challenges while still maintaining high performance in power electronic systems.<br/>

After a total or partial system outage, black-start serves as a critical measure to restore the system to the normal operation. In the later stage of restoration, various types of loads will be energized, the pick-up sequences of which may affect the success probability of the black-start. In this context, a block loading strategy for the inverter-based low-inertia systems is explored, with special consideration given to the inertial support by induction motors. Through detailed analysis, it is shown that initiating induction motors at an early stage leads to improved frequency stability during subsequent loads pick-up. The advantages of prioritizing motor energization are validated from multiple perspectives, including motor starting success rate, the timing of block load pick-up, and the overall system stability. Both simulation results and hardware-in-the-loop validations confirm these observations.

The durability and dependability of lithium-ion batteries (LIBs) play a crucial role in advancing energy storage technologies that power modern applications, including electric vehicles (EVs), consumer electronics, and large-scale energy storage systems. Effective battery health monitoring is essential not only for ensuring safe and efficient operation but also for optimizing battery performance and facilitating second-life applications. Conventional diagnostic techniques, such as voltage and current profiling or impedance spectroscopy, have been widely utilized for LIB assessment. However, these methods often face challenges, such as susceptibility to environmental influences, the need for offline analysis, and dependence on direct electrical connections, limiting their suitability for real-time monitoring. Acoustic Emission (AE) technology has gained attention as a promising, non-destructive approach for real-time monitoring of LIB degradation. By detecting mechanical waves generated during battery operation, AE provides insight into internal structural changes and helps identify key degradation phenomena, including electrode cracking, gas formation, and electrolyte leakage. These acoustic signals offer a unique perspective on stress accumulation and material transformations within LIBs, contributing to a deeper understanding of aging mechanisms. In this study, AE was employed to investigate LIB degradation mechanisms, beginning with graphite/Li and NMC/Li coin cells assembled in a glovebox using LiPF6 in a 1:1 EC:DEC electrolyte. During charging at a 0.5 C-rate, a differential wideband sensor was affixed to the coin cell surface to capture AE signals. The recorded acoustic fluctuations were analyzed, and identical coin cells were aged under similar conditions for validation. Observations revealed significant graphite exfoliation at the fully charged state, with an amplitude of 65 dB. Incremental analysis indicated that the highest amplitude occurred at the peak value, corresponding to the phase transition point, suggesting a strong correlation between AE signals and structural changes during cycling. Post-mortem analysis was conducted to establish correlations between AE signals and electrode structural changes, providing a preliminary link between acoustic signatures and degradation processes. Subsequent experiments focused on commercial LIBs, where testing was carried out within a specially designed foam enclosure to minimize background noise. Advanced digital processing techniques were applied to the AE data to filter out interference and categorize acoustic events based on coin cell spectra. Initial results suggest that AE signals, such as those associated with microcracking, provide distinct markers of electrode degradation. These findings demonstrate AE’s potential as a diagnostic tool for tracking LIB health and detecting critical aging phenomena. Future research will aim to establish more precise correlations between AE events and specific electrochemical reactions occurring within LIBs. By integrating AE with complementary characterization techniques, a more comprehensive understanding of battery aging mechanisms can be achieved. Overall, this study underscores the potential of AE technology to transform LIB health monitoring by providing a real-time, non-invasive, and scalable diagnostic solution. This advancement contributes to improving battery reliability, extending operational lifetimes, and supporting the development of more sustainable and efficient energy storage solutions for future applications.

To evaluate the performance of dual-active-bridge (DAB) converters across various topologies and control schemes for optimal design, this article proposes a generic explicit digital model applicable two-level (2L)/three-level (3L) half-bridge (HB), full-bridge (FB), and three-phase (3P) topologies with a unified control structure. Voltage and current expressions for a single bridge leg considering both 2L and 3L topologies are developed in a generalized manner, and thus the model of DAB topologies with different number of legs can be constructed by superimposing the corresponding number of individual bridge leg models. Subsequently, the digital model, i.e., discrete-time model of DAB converters with different topologies and control configurations, is derived based on the circuit differential equations and a unified closed-loop control system by applying backward Euler method. Therefore, both steady-state and dynamic performance of DAB converters can be predicted in the proposed model. Owing to the analytical formulation of operating parameters and generic expressions for different topologies and control, the calculation speed of the proposed digital model can be accelerated compared to commercial simulation platforms such as MATLAB/Simulink and PLECS, and the design efficiency can be significantly enhanced, especially when it eliminates the need for frequent manual adjustments of topologies, modulation, and loss-thermal models of power devices. Simulation and experimental tests validate that the digital DAB model can achieve high accuracy under various topologies with fast execution speed.