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In the literature, giant magnetoresistive (GMR) point field detectors (PFDs) were integrated in terminals of Si IGBT modules for galvanically isolated current sensing in machine drives. This work presents a PFD-based current sensing system that can be fully integrated in the direct bonded copper (DBC) region of SiC power modules. The physics of phase shift errors caused by the Nickel (Ni) plating in the SiC power module is investigated. To address current sensing phase errors, a real-time phase shift reduction method is proposed. A bandwidth extension method is proposed to meet the sensing requirement of SiC devices that can switch at tens of kilohertz. The phase shift reduction and bandwidth extension methods are experimentally combined to sense the currents in the SiC DBC regions. The proposed current sensing has high bandwidth, minimal phase errors and low position sensitivity. The sensed currents can be used for high performance control and protection of SiC module-based converters.

This article develops the techniques for actively tracking response shifts, induced by thermal–mechanical degradation over components lifetimes’, in spatiotemporal thermal response dynamics. The methodology considers both boundary (e.g., cooling) and internal (e.g., voiding) sources of degradation, and it is considered in the context of power semiconductor devices and packages, including power modules. This article quantifies the transient thermal response sensitivity to degradation using electrothermal impedances viewed with key frequency response function (FRF) metrics over wide dynamic ranges. A developed sensitivity analysis is applied using models and experimental evaluation to relate temperature sensing spatial location, harmonic content of semiconductor device losses, and source of degradation in terms of normalized FRFs that are rapidly interpreted. Complementary loss model parameter sensitivity analysis reveals the advantages in tracking variation in thermal FRF phase delay, rather than amplitude. Finally, to complement pure-FRF approaches for sensing degradation, which use nonparametric data, a method for directly estimating degradation-sensitive physical parameters, in real time, is developed. Experiments demonstrate the automatic estimation of a thermal resistance parameter.

This paper develops a real-time loss minimizing control technique on induction machines for dynamic load profiles. Steady-state loss minimization has been well addressed in the literature. However, when the steady-state optimal stator flux linkage is applied to highly dynamic load profiles, more losses are induced during transients due to the slow rotor flux dynamics. Several heuristic methods have been developed for real-time loss reduction, but they are not designed for minimum losses. Loss-minimizing flux trajectories have been generated by dynamic programming but require prior information of load profiles. In this paper, a real-time loss minimizing control technique is developed for applications without prior information of load profiles. It resembles the loss-minimizing stator flux trajectory generated by a modified dynamic programming method, which generates the best practical solution for unknown load profiles. The steady-state optimal solution for the stator flux linkage is derived based on the induction machine loss model. Both simulation and experimental results demonstrate the energy saving capability of the proposed method.

This article proposes a high-frequency injection based dq -inductance estimation technique for synchronous machines. The d- and q -axis inductance is estimated using a single HFI between d and q axes, i.e., 45 $^\circ$ injection angle. The d - and q -axis incremental inductance variation over four quadrants dq -plane operating condition is evaluated. The proposed technique can operate in real-time without a controlled position or velocity from the load side. Neither previous knowledge of machine parameters nor computationally expensive regression processes are required. The proposed technique can be used to evaluate the sensitivity of inductive saliency based self-sensing to determine preferable self-sensing operating conditions for permanent magnet synchronous machines.

This article presents a method for designing converter systems embedding power modules for a specified degradation monitoring performance in real-time applications. It builds upon prior work which identified specific variations in three-dimensional transient heat transfer with interface and interconnect state-of-health. This article contributes a joint, module-converter concurrent design method to quantify opportunities and limits in using chip-based temperature sensing to integrate electrothermal impedance spectroscopy in situ . Challenges intrinsic to modules, such as many, closely packed heat sources, are quantified. This article also examines spatial degrees-of-freedom for placing additional degradation sensing temperature detectors. Experimental measurements of transient thermal frequency response show trends that can be exploited to push temperature sensors against their signal-to-noise ratio limits. Overall, the design method relies on circuit topology and modulation details; it is directed toward early-stage converter development. To that end, an included harmonic loss modeling step immediately provides a designer with feedback about the feasibility of a degradation sensing concept.

This article introduces new technologies for monitoring thermal response and life-time varying parameters of power electronic modules in real time without interrupting normal converter operation. The technologies are embedded in an adaptive thermal observer, which integrates temperature measurements and electrothermal models to estimate device losses and temperatures at reliability-critical locations of the power module. The observer structure includes a model reference adaptive system for adaptively calibrating device switching-loss models. This improves thermal monitoring accuracy, avoids time-consuming offline calibrations, and creates the opportunity for efficiency estimations during power module operation. The adaptive observer together with small-signal loss-excitation and system-identification technologies extract the thermal impedance of the power module in magnitude and phase over multiple frequency decades. This in situ thermal impedance spectroscopy has the unique feature of continuously providing information on the thermal interface of the power devices without interrupting normal inverter operation. The extracted information, i.e., life-time varying electrical and thermal parameters, enables diagnosing power module state-of-health with improved accuracy compared to prior technologies. It even allows separating different degradation effects, such as bond wire lift-off, device and base-plate solder delamination as well as deterioration of the convection process. With these new features, next generation monitoring systems can extract thermal response and degradation and thus protect power modules from severe thermal stress and overload. Furthermore, the obtained state-of-health information can be selectively used to reduce thermal stress and to schedule predictive maintenance leading to a safer and more reliable operation of future converter systems.

Self-sensing control at zero and low speed has been widely implemented and studied by many researchers. This technique is based on injecting a high-frequency voltage or current into the motor to estimate the motor position and speed from the measured motor quantities like current or voltage. Tracking the motor back-EMF or flux signal has been used to control motors during medium- and high-speed operations. This article proposes a high-frequency flux injection (HFFI) based self-sensing using deadbeat-direct torque and flux control to control permanent magnet servo motor at zero and low speed with ideally zero torque ripple, unlike the standard current or voltage injection techniques. The HFFI is combined with a back EMF self-sensing technique to control the motor during medium- and high-speed operations. This article also proposes a method for a smooth transition between these two methods. The proposed controller is used to control different types of slightly salient servo motors during dynamic servo operations.

High-frequency injection (HFI) is widely used for zero-to-low speed self-sensing in machines with saliency. HFI algorithms use inductive saliency in the d- and q-axes to estimate the rotor position in permanent magnet synchronous machines (PMSMs). Generally speaking, surface PMSMs (SPMSMs), which are designed without inductive saliency, are not suitable for HFI inductive based self-sensing. In this article, a method to enhance HFI algorithms at zero-to-low speed for classically designed SPMSMs with low inductive saliency is presented. The proposed method is based on using intentional magnetic saturation under flux-intensifying (FI) operation, which will temporarily enable robust self-sensing operation in the zero-to-low speed region in machines that are not suitable for traditional HFI self-sensing.

This paper develops impedance spectroscopy for characterizing transient heat transfer in assembled power semiconductor converter systems. The method addresses limits associated with traditional methods, for e.g., data sheet transient thermal impedance curves are step responses that only characterize the junction-to-case spatial-domain segment. The presented method utilizes an actively switching semiconductor as a controlled modulator of dynamic loss (heat) injections, along with multiple temperature measurements, to form spatial electrothermal impedance frequency response function (FRF) models. Complementary investigations of numerical and analytical modeling methods yield a general, compact thermal model template, for interpreting measured FRFs. A pulsewidth modulated power converter with integrated die and heat sink temperature sensing was characterized with the spectroscopy method. Obtained ambient-referred and relative FRFs describe transient heat transfer, including fast (die-level) and slow (sink-level) modes, over frequency decades with coherence. The FRFs were parameterized and interpreted using the derived compact thermal model.

This paper presents a methodology for real-time monitoring of 3-D temperature distributions and device losses within power electronic modules. It allows precise thermal management, empirical lifetime prognosis, and detection of critical degradation of the power module. By effective combination of thermal 3-D finite difference modeling, parametric loss models, and model truncation techniques, a compact thermal real-time model is derived. It enables the computation of device losses and temperatures at critical locations within a power module, e.g., at the devices, solder interfaces or the base plate, on a conventional digital signal processor. The real-time model as well as real-time junction temperature information are combined in a new Luenberger-style observer structure. Applying bandwidth partitioning, the observer estimates the temperatures throughout the power module every switching period and averaged over one excitation period with nearly zero lag, even if the junction temperature measurement exhibits delays and has noisy signals. Furthermore, it estimates errors in the loss prediction process that can be tracked over the lifetime of the power module to detect degradation of the devices or the power module. The observer and its features are experimentally evaluated under realistic operating conditions on a load emulator using a state-of-the-art automotive power module.

This paper proposes a methodology for active thermal control of power electronic modules in ac applications, which includes a loss manipulation unit, a thermal observer structure, and an active thermal cycle reduction algorithm. It aims to reduce the thermo-mechanical strain in the inter-connects of the module in order to enhance its reliability and lifetime. The loss manipulation unit operates in a minimally invasive manner by manipulating adaptive gate resistances and the pulsewidth modulation frequency. This allows the individual thermal control of multiple devices within a power module, which has not been achieved in prior work. A thermal observer structure that estimates averaged junction temperatures by combination of a thermal model and sensor information is introduced. The observer technology makes this paper the first to realize closed-loop control of averaged temperatures achieving an increased robustness and insensitivity to modeling errors. A key element of the active thermal cycle reduction algorithm is the virtual heat sink that derives feasible and stress-relieving thermal trajectories. The trajectories are applied with a unique thermal feedback control that smoothly manipulates the averaged junction temperature of the power module even in the presence of loss manipulation limits. The active thermal control methodology is evaluated experimentally with a state-of-the-art insulated-gate bipolar transistor (IGBT) power module.

Flux weakening techniques have been developed for field-oriented control (FOC) drives to achieve the maximum torque capability above the base speed. Deadbeat-direct torque and flux control (DB-DTFC) has the advantages of precise torque and flux control and reduced parameter sensitivity compared to FOC, thus it has the benefit of more consistently achieving the maximum torque capability in the flux weakening region more accurately. This paper introduces a flux weakening strategy for DB-DTFC. Considering voltage and current limits, a simple solution to the optimal trajectory for the stator flux magnitude is derived to achieve the maximum feasible torque over the entire operating range. Results show that the speed control is extended to a significantly higher range beyond the base speed. Torque control is less sensitive to machine parameters and has better dynamics in the flux weakening region compared with the traditional FOC drives. Self-sensing is also investigated in the flux weakening region. Challenges of self-sensing are addressed to significantly extend the high-speed operating range.

Six-step modulated drive systems have been shown to have higher power density and lower switching loss than pulsewidth modulation drive systems. It has also been shown that by manipulating the dc bus voltage, six-step mode can drive permanent magnet synchronous machines (PMSMs) over a wide speed range, and maintain the machine operating point on the maximum torque per ampere curve below the base speed to reduce the machine copper loss. However, high torque ripple exists while in this type of six-step mode. This paper develops the control design methodologies to leverage the variable and fast dc bus manipulation, provided by two-step finite-settling-step dc-to-dc converter control, to minimize torque ripple in six-step PMSM drives. Two torque control algorithms: existing voltage angle based torque control and deadbeat-direct torque and flux control are used to evaluate torque ripple reduction capability and energy savings potential of six-step PMSM drive systems.

Variable magnetization pattern permanent magnet synchronous machines (VMP-PMSMs) capable of dynamic changes in the magnetization spatial distribution are discussed in this paper. VMP-PMSMs are able to change the harmonic components in the air gap magnetic flux density due to the magnet by intentional demagnetization; hence, they can effectively manipulate the torque ripples and losses according to the required operating points. The objective of this paper is to provide a procedure to design VMP-PMSMs that can have both the sinusoidal and the trapezoidal back EMF waveforms by switching magnetization pattern. The performance of the designed VMP-PMSM following the reported procedure is confirmed through experiments as well as finite element analysis (FEA) simulations in terms of the back EMF shaping, torque ripple reduction, and loss reduction. Loss analysis of VMP-PMSMs is also given as contrasting with variable flux permanent magnet machines (VF-PMSMs), showing that VMP-PMSMs can reduce more losses than VF-PMSMs with the same torque density.

Energy consumption and efficiency of electrical drives is becoming an increasingly important issue. This encourages many researchers to develop new control techniques to reduce the energy consumption in electrical drives. Some of those techniques are more effective than others; some of them can save energy but will affect the response of the drive. Deadbeat-direct torque and flux control has the fastest possible response, allowing direct and independent control of the actual motor states. Using this controller, it is possible to select the optimum stator flux linkage in each switching period to minimize the motor losses dynamically. Many algorithms were derived for motors that are not operating at the voltage limit. This paper will present an algorithm that can be used to minimize motor losses without affecting electrical drive performance. The proposed algorithm works even at the voltage limit during flux weakening operation, it is also easy to implement, doesn't require any lookup tables that require significant effort to obtain, can be applied to any kind of permanent magnet motors, and is feasible in real time for different operating conditions.

This work investigates the modeling of lithium-ion batteries (LIBs) with a recurrent neural network (RNN), rather than with an equivalent circuit or similar type model as is typically used. The RNN is trained with dynamic battery data, such as vehicle drive cycle test results. Specialized characterization tests and model parameterization are not necessary, simplifying the process of battery modeling. A compact unified methodology consisting of an RNN with gated recurrent unit and deep feature selection structures is utilized. A total of two RNNs are evaluated, one with current as the input and another with power as the input. Both RNN forms accurately model LIB dynamic responses including battery nonlinear behavior at different temperatures. The models are compact in size, require fewer characterization tests compared to conventional equivalent circuit models, and can be further used as an LIB simulator in model-based design and hardware-in-loop applications to test battery management systems and other electronic components.

Coater sections are examples of multi-span web transporting systems, with dynamic characteristics related to the sheet properties and control schemes. This paper first describes and analyzes a set of field records of a production 2-coater section paper machine. Then, extending the 1-coater section model developed in a related paper, a precise simulation model of a 2-coater section is implemented. This model is used to evaluate the beginning of the coating process and the effect on the section responses of different bandwidth settings in the tension and speed controllers. Results show agreement with the field records and demonstrate that the developed model is a powerful tool to analyze and understand the behavior of coater sections during both, transient and steady state conditions.

This paper develops a technique, requiring no dedicated temperature sensing calibration step, to rapidly characterize transient heat transfer in packaged, power semiconductor components. It is presented as an alternative to traditional step response characterization methods by exploiting the phase delay metric native to frequency response function (FRF) analysis in the field of system identification. The paper introduces electrothermal engineering steps needed to design the measurement system. It presents aspects of power device physics and dynamic analysis to identify design space in which FRF data extracted from experiments are insensitive to potential unknowns. Power electronic circuitry, providing the needed, periodic heat actuation, and probing, allowing for simple reconstruction of transient temperature data in post-processing, are introduced. The developed method is leveraged in-lab to make a key measurement confirming high-frequency-only thermal FRF sensitivity to component die-attach, highlighting the opportunity to achieve localized, power electronic converter degradation sensing in situ.

Past work has demonstrated that arrays of magnetoresistive (MR) point field detectors (PFDs) can be integrated into power modules and busbars for compact current sensing in multiphase power electronic systems. This paper presents a methodology to design three-phase full-bridge power modules with integrated current sensing using a single 3-D PFD. Frequency-dependent skin and proximity effects are investigated in the power module to increase the magnetic field bandwidth. Designs for leadframes, terminals, and baseplates are recommended for producing a net 3-D magnetic field that includes cross-coupling from all three phase currents. A 3-D field decoupling technique, presented in previous papers, is used to decouple the phase currents from the net magnetic field sensed by the 3-D PFD. Three-phase high-bandwidth current sensing is experimentally implemented in custom-designed leadframes with cross-coupled field decoupling using a single 3-D MR PFD. This integrated current sensing method provides advantages in power density, cost, manufacturing, and implementation.

In an inductive wireless power transfer system, unavoidable lateral misalignment between the transmitter and the receiver leads to reactive power, which reduces the powertransfer-efficiency and limits the maximum output power under given input voltage. A tunable capacitor provides access to achieve low reactive power and maintain high power-transfer-efficiency. In this paper, the effects of misalignment on power transfer performance is investigated. A conventional capacitor tuning method is analyzed, and its limitations are identified. An innovative low loss online capacitor tuning method is proposed to automatically achieve low reactive power and maintain high power-transfer-efficiency under misalignment. The proposed designs are evaluated via simulation.

In an inductive wireless power transfer (IWPT) system, an “I” type magnetic shielding structure was proposed to simultaneously reduce the air-gap center region magnetic and electric fields without degrading the coil-to-coil efficiency. However, the proposed structure is difficult to implement due to the requirement of enormous ferrite materials. In this paper, the “I” type magnetic shielding design is optimized for the reduction of ferrite usage, cost, weight, and easy implementation, while maintaining nearly the same field distributions and power transfer efficiency. The optimized designs can reduce the ferrite usage by nearly 70% with nearly the same performance. The proposed methods are evaluated with a 2 kW, 30 cm transfer distance design example using finite element analysis (FEA).

Surface spiral winding (SSW) has been demonstrated to achieve low skin and proximity effects copper losses, and low air-gap magnetic flux density in MHz, kW level inductive wireless power transfer systems. The dielectric losses are still the limiting factor to further improve the coil-to-coil efficiency. In addition, high spatial voltage stress between the first turn and the end turn limits the maximum transferable power due to the voltage breakdown. This paper develops alternative coil configurations to reduce the copper loss, the dielectric losses, and the spatial voltage stress. Through emulating SSW using copper tubing, the dielectric losses and the spatial electric field between adjacent turns are reduced simultaneously. Two surface spiral parallel winding designs are proposed to reduce the equivalent series resistance and improve the coil-to-coil transfer efficiency. A surface spiral antiparallel winding design is proposed to equalize dynamic voltage stress between adjacent turns and improve power scalability while maintaining high coil-to-coil transfer efficiency.