Intelligent and pragmatic state-of-health (SOH) estimation is critical for the safe and reliable operation of Li-ion batteries, which recently have become ubiquitous for applications such as electrified vehicles, smart grids, smartphones,... more
Intelligent and pragmatic state-of-health (SOH) estimation is critical for the safe and reliable operation of Li-ion batteries, which recently have become ubiquitous for applications such as electrified vehicles, smart grids, smartphones, as well as manned and unmanned aerial vehicles. This paper introduces a convolutional neural network (CNN)-based framework for directly estimating SOH from voltage, current, and temperature measured while the battery is charging. The CNN is trained with data from as many as 28 cells, which were aged at two temperatures using randomized usage profiles. CNNs with between 1 and 6 layers and between 32 and 256 neurons were investigated, and the training data was augmented with noise and error as well to improve accuracy. Importantly, the algorithm was validated for partial charges, as would be common for many applications. Full charges starting between 0 and 95% SOC as well as for multiple ranges ending at less than 100% SOC were tested. The proposed C...
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This paper proposes a way to augment the existing machine learning algorithm applied to state-of-charge estimation by introducing a form of pulse injection to the running battery cells. It is believed that the information contained in the... more
This paper proposes a way to augment the existing machine learning algorithm applied to state-of-charge estimation by introducing a form of pulse injection to the running battery cells. It is believed that the information contained in the pulse responses can be interpreted by a machine learning algorithm whereas other techniques are difficult to decode due to the nonlinearity. The sensitivity analysis of the amplitude of the current pulse is given through simulation, allowing the researchers to select the appropriate current level with respect to the desired accuracy improvement. A multi-layer feedforward neural networks is trained to acquire the nonlinear relationship between the pulse train and the ground-truth SoC. The experimental data is trained and the results are shown to be promising with less than 2\% SoC estimation error using layer sizes in the range of 10 - 10,000 trained in 0 - 1 million epochs. The testing procedure specifically designed for the proposed technique is e...
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Varying the operating frequency helps dual-active bridge topologies increase the system efficiency since the soft-switching is regained at low-load condition. This paper proposes a conduction-loss-based variable frequency modulation (VFM)... more
Varying the operating frequency helps dual-active bridge topologies increase the system efficiency since the soft-switching is regained at low-load condition. This paper proposes a conduction-loss-based variable frequency modulation (VFM) that decouples the phase shift from the frequency control that conventional VFM applies. The power losses for the shared-bus battery balancing topology are elaborated as switching frequency varies. The results show that increasing the operating frequency within reasonable boundaries can benefit not only the switching loss but also the conduction losses. The switching loss is nearly constant, whereas the conduction losses decrease significantly. A factor of output power and transformer current, namely power-per-ampere, is derived as a function of operating conditions and phase shift independent of switching frequency. The operating setpoints are selected to minimize the factor using both online and offline optimizations. The proposed control strategy outperforms constant frequency modulation by up to 30% below 30% rated power. Furthermore, compared with conventional VFM, the proposed method improves the efficiency of the system under test by 1.5% below 50% normalized power, with significantly less computational resources needed.
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This paper deals with an “active flux” model-based approach for state estimation of Permanent Magnet Synchronous Motors to build up sensorless drives. The active-flux vector is aligned to the rotor d-axis for all synchronous machines. In... more
This paper deals with an “active flux” model-based approach for state estimation of Permanent Magnet Synchronous Motors to build up sensorless drives. The active-flux vector is aligned to the rotor d-axis for all synchronous machines. In this way, the rotor position and speed observer seems more amenable to a wide speed range, with smaller dynamic errors. A Moving Horizon Estimation algorithm, an optimization-based scheme that yields good performance, is applied for the speed and rotor position estimation. Under assumptions, an optimal problem of Equality Constrained Quadratic Programming type has been solved each iteration. The algorithm has been efficiently implemented and tested for both Surface and Interior Permanent Magnet Synchronous Motors, demonstrating the real-time feasibility the proposed approach at 10 kHz sampling rate.
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This research studies a discrete time optimization-based position estimation strategy. The method accomplishes approximation over nonlinear dynamic models, making it convenient to take the magnetic saturation into account. The dynamic... more
This research studies a discrete time optimization-based position estimation strategy. The method accomplishes approximation over nonlinear dynamic models, making it convenient to take the magnetic saturation into account. The dynamic model is written in the virtual flux domain, ending up with affine dynamic constraints and nonlinear output constraints. The performance of the observer is tested incorporated with vector control. The result shows the estimation strategy with higher variable dimension is capable of accurate parameter and state reconstruction. Comparing to prior work, the proposed method gains better estimating precision, more flexibility and higher stability. In particular, there is significant improvement in estimation accuracy at low speed - peak noise 0.0095 rad (<0.424 rad), standard deviation 0.0020 rad (<0.038 rad) in position estimation and peak noise 1.50 rad/s (<13.17 rad/s), standard deviation 0.587 rad/s (<6.877 rad/s) in speed estimation.
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A novel unified position sensorless observer is proposed using homotopy continuation. A single observer is used to estimate the rotor position and speed at high speed, low speed, and standstill. The position and speed are treated as... more
A novel unified position sensorless observer is proposed using homotopy continuation. A single observer is used to estimate the rotor position and speed at high speed, low speed, and standstill. The position and speed are treated as independent variables such that the PMSM dynamic equation is a parametrized algebraic function f where the zeros identify the position and speed estimate. A homotopy is identified that maps the zeros of f at sampling time instant k − 1 into the zeros of f at sampling time instant k. As the algebraic equation has multiple zeros, the homotopy is designed to identify the closest zero that, assuming reasonable sampling, identifies the correct position and speed. Benefits of the proposed method are instantaneous estimation and lack of convergence transients once a rough estimate is available through initial position estimation with polarity detection. The concept is validated at low and high speed using high-fidelity simulations.
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Demand for the grid state estimation with partial power network observation is growing rapidly with the increasing amount of distributed energy resources (DER) connected to the grid with incomplete measured information. The grid services... more
Demand for the grid state estimation with partial power network observation is growing rapidly with the increasing amount of distributed energy resources (DER) connected to the grid with incomplete measured information. The grid services that could be provided by these DER, such as electrical vehicles (EVs), have the potential to affect the resilience and efficiency of the grid. This paper proposes a constrained optimization solver based on the AC power flows to recover the incomplete information of the grid. Further reactive power constraints following the specifications in IEEE 1547 are added to the solver to explore the effects of adding grid services to the steady-state microgrid.
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A novel optimization-based sensorless technique for Induction Machines is presented in this work. The algorithm is able to estimate speed and position instantaneously (limited only by the Nyquist frequency and the PLL bandwidth) at... more
A novel optimization-based sensorless technique for Induction Machines is presented in this work. The algorithm is able to estimate speed and position instantaneously (limited only by the Nyquist frequency and the PLL bandwidth) at standstill low and high-speed. A cost function is introduced based on the dynamic machine model. The stability analysis of speed and position estimation shows whether the system is convex by solving the Hessian matrix of the cost function. The method is unique for the entire speed range, in which high-frequency signal is injected to the machine terminals at low speeds, to increase the convex region of the cost function.
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This paper proposes a way to augment the existing machine learning algorithm applied to state-of-charge estimation by introducing a form of pulse injection to the running battery cells. It is believed that the information contained in the... more
This paper proposes a way to augment the existing machine learning algorithm applied to state-of-charge estimation by introducing a form of pulse injection to the running battery cells. It is believed that the information contained in the pulse responses can be interpreted by a machine learning algorithm whereas other techniques are difficult to decode due to the nonlinearity. The sensitivity analysis of the amplitude of the current pulse is given through simulation, allowing the researchers to select the appropriate current level with respect to the desired accuracy improvement. A multi-layer feedforward neural networks is trained to acquire the nonlinear relationship between the pulse train and the ground-truth SoC. The experimental data is trained and the results are shown to be promising with less than 2\% SoC estimation error using layer sizes in the range of 10 - 10,000 trained in 0 - 1 million epochs. The testing procedure specifically designed for the proposed technique is e...
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Moving Horizon Estimators (MHE)solve an optimization problem to estimate unknown states or parameters based on a sequence of measurements containing disturbances and noise in nonlinear systems subject to input and state constraints. This... more
Moving Horizon Estimators (MHE)solve an optimization problem to estimate unknown states or parameters based on a sequence of measurements containing disturbances and noise in nonlinear systems subject to input and state constraints. This research applies MHE to estimating the nonlinear behavior of interior-mount permanent magnet synchronous machines (IPMSM). The MHE estimates a disturbance term that reppresents the speed-dependent nonlinear terms of the machine model and can be interpreted as extended back-EMF. The formulation is based on a cost function that matches the measurements to the model formulation and an explicit regularization penalty is added. The term is interpreted as a gain that balances estimation accuracy with noise rejection. We demonstrate that our formulation can be solved in realtime and is effective in estimating the disturbance term on an experimental test bench both in terms of noise rejection and estimation accuracy.
To improve power density and efficiency, a critical soft switching principle with optimal-frequency model predictive control method is proposed in this paper for DC/DC power converter. Firstly, this paper analyzes the boundary constraints... more
To improve power density and efficiency, a critical soft switching principle with optimal-frequency model predictive control method is proposed in this paper for DC/DC power converter. Firstly, this paper analyzes the boundary constraints of critical soft switching that are derived with the key parameters of the interlock time and threshold current for typical SiC and GaN devices. Then, according to the derived critical soft switching constraints, two optimal-frequency control methods are proposed based on model predictive control (MPC) to eliminate the turn-on losses especially during the transient period. Compared to the traditional PI controller, the efficiency can be further improved during the reference variation period, because of the fast response of MPC. Finally, the test results verify the theoretical analysis.
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This paper analyzes direct position and speed estimation from a control theoretical and numerical standpoint. The paper develops the theory of local identifiability and defines the conditions such that position and speed can be identified... more
This paper analyzes direct position and speed estimation from a control theoretical and numerical standpoint. The paper develops the theory of local identifiability and defines the conditions such that position and speed can be identified uniquely based on a sufficiently accurate guess. Local identifiability typically holds at nonzero machine speeds and zero speeds with any perturbation, e.g. an injected high frequency signal in pwm control or a random switching ripple in direct control (except in isotropic machines). The position and speed is identifiable in more than 98.5% of feasible operation points “instantaneously”, and can be extrapolated from past estimates in the remaining cases. Finally, numerical solving strategies are studied and a combination of the Newton and conjugate gradient method is shown to provide suitable estimates within 1–5 solver iterations depending on the required accuracy.
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A critical soft switching technique is proposed to reduce the switching losses of a bidirectional DC/DC converter. The proposed method can improve the efficiency and the value of passive components will be largely decreased. The paper... more
A critical soft switching technique is proposed to reduce the switching losses of a bidirectional DC/DC converter. The proposed method can improve the efficiency and the value of passive components will be largely decreased. The paper derives the boundary conditions of critical soft switching with the parameters of dead time and threshold current for existing typical SiC and GaN devices. Then, a controlling strategy is developed to estimate and optimize the total power losses of a synchronous DC/DC converter with variable frequency at the given average current and duty cycle. With the combination of critical soft switching and optimal frequency control, the efficiency can be largely improved in every operating point. A power loss curve comparison between the proposed method and hard switching shows that the proposed method can reduce the losses up to 40%. The theoretical results are verified in a rigorous testing procedure.
A battery equivalent circuit model (ECM) is proposed using a novel physics-based diffusion component and N resistor–capacitor (RC) pairs, hence its name the ‘DNRC model’. The DNRC model characterizes ohmic, charge transfer, and diffusion... more
A battery equivalent circuit model (ECM) is proposed using a novel physics-based diffusion component and N resistor–capacitor (RC) pairs, hence its name the ‘DNRC model’. The DNRC model characterizes ohmic, charge transfer, and diffusion overpotentials in the time domain with physically-meaningful circuit elements. Unlike the Warburg impedance, the diffusion component has no need for frequency-domain data and is formulated entirely in the time domain. Physical interpretability is validated by comparison with physics-based model (PBM) generated data. Experimental validation is performed at a wide range of state of charge (SoC) and state of health (SoH) using pulse injection and drive cycle data. The mean absolute percent error is below 0.3% using 5 circuit elements for 4 min of an arbitrary current load. The DNRC model is grounded in physical principles, suitable for real-time estimation, and may form the basis for new approaches to degradation reduction or diagnosis in battery manag...
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Power loss calculations are critical to a power converter design, helping with estimation of efficiency, switch selection and cooling system design. Moreover, power losses in a MOSFET may limit the maximum switching frequency in a power... more
Power loss calculations are critical to a power converter design, helping with estimation of efficiency, switch selection and cooling system design. Moreover, power losses in a MOSFET may limit the maximum switching frequency in a power converter. Switching energy values aren't always available in MOSFET datasheets at all operating points, and calculation of voltage and current rise-time and fall-time is needed. This paper introduces a method to obtain an estimate of switching transition times and power losses, using datasheet parameters, for SiC MOSFETs with non-flat gate-plateau region. Three methods are discussed here, two existing and a proposed method. These methods are used to evaluate a certain MOSFET product, and calculated values are compared with results from PLECS simulation and double pulse test experiment. The proposed method is shown to yield improved accuracy.
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Multiphase systems have the capability to achieve significantly higher drive voltages than what is possible with sinusoidal PWM or linear modulation/nth harmonic injection. However, overmodulation beyond that of the zero sequence yields... more
Multiphase systems have the capability to achieve significantly higher drive voltages than what is possible with sinusoidal PWM or linear modulation/nth harmonic injection. However, overmodulation beyond that of the zero sequence yields large harmonic currents if not implemented properly. This paper presents a scheme that enables the full overmodulation range of the αβ voltage vector to be attained with the minimum theoretical excitation of the components in the higher-order dq (xy) plane(s). First, the maximum limits of overmodulation drive voltage amplitudes are defined for N > 3 phase systems using vector space interpretation of the DC bus voltage constraints. Next, the theoretical lower limits of harmonic sequences required for overmodulation are established for N > 3 phase systems by formulation of a parametric quadratic programming problem. With an overmodulation scheme that uses this optimized solution, a drive system's speed rating is improved due to the increased voltage, as it is with non-optimized overmodulation schemes. However, since the harmonic currents are minimized, the drive voltage improvement is less restricted when taking into account the system's current ratings. The resulting increased range of operation is demonstrated for a 9 phase PMSM model with RMS current constraints and is shown to be supplementary to flux weakening.
Model predictive control and receding horizon estimation are advanced control and estimation techniques for next-generation high performance motor drives. These methods benefit from low noise and accurate system models, which are... more
Model predictive control and receding horizon estimation are advanced control and estimation techniques for next-generation high performance motor drives. These methods benefit from low noise and accurate system models, which are challenging to realize with parameter-based motor models. The idea of virtual-flux, where the machine is modelled with flux instead of current, has been seen as a solution, as the parameters and their nonlinearities can be captured by a function that maps measured current onto the corresponding flux it generates. In this way, all system information can be encoded in a single static function, simplifying the stability and robustness analyses, as well as online computational requirements. Furthermore, virtual-flux modelling allows for many electric machines and even the electric grid to be described in a similar way. This review condenses the results in literature into a uniform virtual-flux framework and explores the applications and potential of model predictive control and receding horizon estimation. The combination of these concepts is shown to strongly benefit their respective problems, ranging from finite control set and convex control set MPC, full and reduced phase current sensor set flux estimation, and position and speed co-estimation.
Inductor design can be a process of repetitive core searching and iterative turn and airgap calculation, where every decision to be made involves a trade-off in terms of power loss, cost and power density. This paper deeply discusses the... more
Inductor design can be a process of repetitive core searching and iterative turn and airgap calculation, where every decision to be made involves a trade-off in terms of power loss, cost and power density. This paper deeply discusses the inductor design for a transformerless DC EV battery charger where inductance and operating DC bias are required to be high ($\mathrm{500}\ \ \mu \mathrm{H}$ and 32 A). The design of the charger's filter is discussed to provide the values of the passive components and to motivate the inductor design. Two commonly used but seldom compared winding options, Litz wire and printed circuit board, are both designed and examined with respect to power loss and difficulty of the fabrication. Through tuning of the trace width and copper weight, the PCB design can provide similar performance to the Litz wire configuration, at higher cost and increased manufacturing complexity. In order to verify the text-colorblacktheoretical calculations, high-fidelity 3D finite element analysis is performed for both inductor types. After comparison, the Litz wire implementation was chosen for its reduction in power losses, cost and manufacturing complexity. The Litz wire inductor is assembled and tested on a transformerless DC charger platform with ≥ 99% efficiency at 11 kW and ≥98% efficiency at up to 22 kW.
The transformer is one of the most bulky, expensive and lowest efficiency components in a typical electric vehicle charging system. Its removal is conducive to enabling greater proliferation of charging infrastructure and the adoption of... more
The transformer is one of the most bulky, expensive and lowest efficiency components in a typical electric vehicle charging system. Its removal is conducive to enabling greater proliferation of charging infrastructure and the adoption of electrified vehicles. However, simply removing it can lead to common mode voltage and leakage current issues that present a safety hazard. To address this and to be compliant with international standards, a transformerless electric vehicle charging system enabled by control is proposed without need for additional components. This is achieved by connecting the three-phase filter capacitor neutral point to the DC negative, which allows the zero sequence voltage to be controlled, thereby mitigating leakage currents. Simulations show that the leakage current of the proposed transformerless charger can be made standard compliant with the topology while experiments provide validation through zero sequence voltage and active and reactive power steps. The results demonstrate that the transformer can be removed from electric vehicle chargers.
The advent of Silicon-Carbide and Gallium-Nitride MOSFETs offers potential to realize higher energy density power converters operating at increased switching frequencies. The maximum switching frequency in a power converter is limited by... more
The advent of Silicon-Carbide and Gallium-Nitride MOSFETs offers potential to realize higher energy density power converters operating at increased switching frequencies. The maximum switching frequency in a power converter is limited by the ability of the switching device package to dissipate its switching and conduction losses. At a given value of drain-source voltage and current, the turn-on losses in a MOSFET are usually greater than the turn-off losses. This paper introduces a soft-switching technique for power converters using wide bandgap devices to replace the larger turn-on losses with smaller turn-off losses and thus reduce the power dissipation of the overall system. The turn-off losses are further reduced with use of additional capacitance across the MOSFET drain-source terminals. Results from an analytical model, LTSpice simulation and experimentation are shown to match closely, with a significant reduction in overall system losses.
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A variable-switching constant-sampling frequency critical soft switching model predictive control (VSCS-MPC) method is proposed in this paper to improve the dynamic behavior, efficiency and power density of the DC/DC power converters.... more
A variable-switching constant-sampling frequency critical soft switching model predictive control (VSCS-MPC) method is proposed in this paper to improve the dynamic behavior, efficiency and power density of the DC/DC power converters. Firstly, this paper analyzes the boundary constraints of critical soft switching that are derived with the key parameters of the interlock time and threshold current for typical SiC and GaN devices. Then, the VSCS-MPC method is proposed for synchronous DC/DC converter. Both the current source load and resistive load converters are validated with the proposed MPC method. VSCS-MPC includes two controlling parts. First is the frequency controller to maintain the critical soft switching operation by adjusting the switching frequency based on the pre-defined boundary conditions with a constant sampling frequency. A discretized frequency controller is developed to improve the stability of the system by maintaining a fixed sampling frequency. Second part is the model predictive controller to track the output voltage/current and maintain critical soft switching during dynamic periods. The explicit optimization and oversampling methods are applied in the MPC controller to meet the high frequency demand. A large current ripple ($\triangle i_L$ $\ge$ 200 %) is introduced to achieve the critical soft switching and reduce the inductance. The switching losses are decreased by the frequency controller and the critical soft switching is maintained especially in dynamic periods due to the fast response of MPC.
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This paper proposes a modeling and control approach for the three-level DC-DC converter. The converter is described in a sum and difference (ΣΔ) framework. It is shown that the formulation is useful to model the inverter and derive... more
This paper proposes a modeling and control approach for the three-level DC-DC converter. The converter is described in a sum and difference (ΣΔ) framework. It is shown that the formulation is useful to model the inverter and derive design-specific equations. The Σ component is responsible for the inductor current, i.e. the power flow, and the Δ component is used to balance (or unbalance) the DC-link capacitor voltages. It is shown that there are cross-coupling terms between the Σ and Δ axes that can be compensated. The proposed model is validated using high fidelity simulations with a proportional-integral controller. Two- and three-level converter operation is shown and it is proven that the passive components can be reduced by 50% to 75% using three-level operation without affecting the control performance. The control is verified by introducing load current and DC voltage steps.
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The active or passive decoupling method has to be utilized to deal with the second-order harmonic existing in the DC-bus of the grid-tied single-phase inverters. Compared with the active decoupling method, the passive decoupling method is... more
The active or passive decoupling method has to be utilized to deal with the second-order harmonic existing in the DC-bus of the grid-tied single-phase inverters. Compared with the active decoupling method, the passive decoupling method is simpler, cheaper and more reliable. The electrolytic capacitors are usually used in the DC-bus as typical passive decoupling components. The film capacitors can be added in parallel with the electrolytic capacitor to help filtering out the high frequency harmonics to extend the electrolytic capacitors' life. In addition, the LC resonant filter can be utilized for the decoupling purpose to achieve better performance. However due to the relatively low resonant frequency, it results in large inductance which will significantly increase the size and cost of the system. A current sharing method is proposed in this paper. With this method, an inductor with reasonable size can be utilized in the LC resonant filter to further extend the electrolytic ca...
The performance of rotor position estimation of interior permanent magnet synchronous motor (IPMSM) tends to be negatively impacted by inverter and motor nonlinearities. In low voltage systems, the on-voltage drop of power electronic... more
The performance of rotor position estimation of interior permanent magnet synchronous motor (IPMSM) tends to be negatively impacted by inverter and motor nonlinearities. In low voltage systems, the on-voltage drop of power electronic switches has a significant impact. This paper focuses on compensating nonlinearities in a 48V motor drive intended for hybrid vehicle powertrains with belt-driven starter-generator (BSG). A real-time voltage compensation method is introduced and saturation is addressed with inductance measurements. The effectiveness of the proposed methods is validated and evaluated by the experimental results.
This paper focuses on the transformerless fast charging solution of plug-in electric vehicles (PEV). In a PEV system, the chargers can be classified into three levels: ac level 1 (< 1.92 kW), ac level 2 (< 19.2 kW), dc level 3... more
This paper focuses on the transformerless fast charging solution of plug-in electric vehicles (PEV). In a PEV system, the chargers can be classified into three levels: ac level 1 (< 1.92 kW), ac level 2 (< 19.2 kW), dc level 3 (>19.2 kW) [1]. For the high-power level 3 fast charging system, it is not viable to place an on-board charger due to the volume and weight. We propose two topologies for off-board non-isolated DC charger to provide fast DC charging with high-power (up to 22 kW). The proposed topology includes two stages, AC/DC rectifier and DC/DC converter. According to the grid requirement, the AC/DC rectifier topologies can be divided into single-phase and three-phase applications. For the three-phase grid interface, the design of the DC charger uses the same hardware for both the grid interface and the DC/DC stage. The development and manufacturing costs are reduced due to the symmetric design of the two stages of circuit. The leakage current issue of the non-isol...
This paper proposes a three phase transformer-less inverter to reduce the common mode voltage with hybrid AC/DC bypass circuit in the PV inversion system. The proposed inverter has the advantages of low conduction losses compared to the... more
This paper proposes a three phase transformer-less inverter to reduce the common mode voltage with hybrid AC/DC bypass circuit in the PV inversion system. The proposed inverter has the advantages of low conduction losses compared to the traditional three phase DC bypass inverter. The fluctuation range of the common mode voltage can be reduced to 1/3 of the traditional inverter. Thus, the leakage current will be significantly suppressed. Also, a variation topology of the proposed inverter is shown in this paper. The detailed comparison between the proposed inverter and the traditional three phase three level inverters reveals that the proposed inverter saves 3 switches compared to the NPC inverter and has less conduction losses compared to the DC bypass inverter.
This paper studies the steady-state behavior of Finite Control Set (FCS) Model Predictive Control (MPC) for permanent-magnet synchronous machine (PMSM). The control actuation is formulated as a trajectory tracking problem in the αβ stator... more
This paper studies the steady-state behavior of Finite Control Set (FCS) Model Predictive Control (MPC) for permanent-magnet synchronous machine (PMSM). The control actuation is formulated as a trajectory tracking problem in the αβ stator flux space. The concept of set stability and Control Invariant Set (CIS) is used to determine the smallest possible current, i.e. flux ripple. The best achievable steady state region of the control error is proposed and validated, revealing the maximum switching performance of FCS-MPC. The upper bound of the control error is achieved by constructing a CIS with respect to any reference defined on the equilibrium operating points. The proposed analysis has direct applications since it can be used to predict and optimize the current ripple in real time. Another application is the variation of the sampling frequency to achieve maximum ripple requirements at minimum switching losses.
In this paper, a novel balancing circuit is proposed for battery-balancing auxiliary power modules. By connecting two battery cells on the primary side instead of filtering capacitors, the topology offers features like reduced-cost and... more
In this paper, a novel balancing circuit is proposed for battery-balancing auxiliary power modules. By connecting two battery cells on the primary side instead of filtering capacitors, the topology offers features like reduced-cost and three-mode balancing, including the combination of cell to cell and cell to auxiliary in either power flow direction for each cell within one bridge. A modified phase shift control with asymmetric duty cycle is developed for preventing transformer from saturation, and for adjusting the DC offset current of the transformer to realize different balancing modes. A general design guidance for the passive components of the circuit, such as transformer and output filtering capacitor, is provided for given output power and peak current limitations, inclusive a design example. Three balancing modes are validated at 10 MHz switching frequency.
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In this paper, a virtual-flux finite control set model predictive control (FCS-MPC) strategy of switched reluctance motor (SRM) drives is proposed. This technique uses a flux linkage-tracking algorithm to indirectly control the phase... more
In this paper, a virtual-flux finite control set model predictive control (FCS-MPC) strategy of switched reluctance motor (SRM) drives is proposed. This technique uses a flux linkage-tracking algorithm to indirectly control the phase current. The algorithm is based on an estimated virtual flux obtained from the static characteristics of the machine. A cost function is used to evaluate the switching state that produces the minimum error. A state graph for switching states limitation is also proposed to reduce the number of commutations and computational burden. Simulation results evidence the enhanced performance of the proposed technique with respect to hysteresis control for current tracking using two different current shaping techniques: torque sharing function (TSF) and radial force shaping (RFS).
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In a photovoltaic grid connected system, the attenuation of the common mode voltage is one of the main issues. Many single phase inverters have been proposed to improve the common mode characteristic. However, few studies have been... more
In a photovoltaic grid connected system, the attenuation of the common mode voltage is one of the main issues. Many single phase inverters have been proposed to improve the common mode characteristic. However, few studies have been focused on the topological improvement for common mode behavior of the three phase inverter. This paper proposed two types of novel three phase NPC inverters with low leakage current. The common mode characteristic of the inverter can be improved by the proposed NPC circuit. Firstly, the common mode model of the three phase inverter is analyzed. Then, the improved three phase NPC circuit and the variation topology are introduced with the operating principles. Thirdly, a comparison between the improved NPC inverters and the traditional three phase NPC inverters illustrated that the proposed topologies have the advantages in the aspect of device cost and conduction losses. Finally, the simulation results verified the theoretical findings.
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This article introduces high-performance filter techniques for direct position and speed estimation to augment its robustness against disturbances. The direct estimation concept provides an independent position and speed estimate at each... more
This article introduces high-performance filter techniques for direct position and speed estimation to augment its robustness against disturbances. The direct estimation concept provides an independent position and speed estimate at each sampling instant by solving an optimization problem parameterized with the current, current derivative, and voltage of the same sample. It can operate at any speed employing a voltage injection at low speed or pulsewidth modulated current derivative. A selective filter concept is proposed that discards samples lacking robustness based on cost function properties. The concept is most effective in removing worst case errors and should always be applied. Also, output filter techniques are investigated to improve the estimates. A finite impulse response (FIR) structure is proposed that filters estimates according to a least-square criterion and is effective in reducing average estimation errors. The FIR filter is benchmarked against an enhanced dual phase-locked loop (PLL) filter, which is enabled by direct estimation. The FIR and dual-PLL filters are found to have a 6.8 and 1 kHz practical bandwidth, respectively, while achieving a $< $1% absolute mean position and speed estimation error. Hence, they perform one to two orders of magnitude better than traditional estimation schemes, which typically achieve $< $100 Hz bandwidth at similar errors.
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Abstract Thermoelectric generators (TEGs) can harvest thermal energy from waste heat sources to supply various power levels due to the Seebeck effect. The power generated by a TEG is dependent not only on the temperature difference across... more
Abstract Thermoelectric generators (TEGs) can harvest thermal energy from waste heat sources to supply various power levels due to the Seebeck effect. The power generated by a TEG is dependent not only on the temperature difference across them but also on the electrical load applied. Typically, waste heat sources have variable operating conditions which means maximum power point tracking (MPPT) must be employed through the use of power converters to produce the desired operating point of the system and thus increase the system efficiency. This paper presents a new MPPT scheme which has not been previously applied to thermoelectric generators, the high frequency injection (HFI) scheme to achieve a fast and accurate tracking of the maximum power operation point for TEGs. The proposed MPPT scheme is implemented with a power converter, and the tracking scheme performance is experimentally evaluated on a commercial TEG module through three different experiments. The proposed scheme is also compared to the most commonly used MPPT scheme for TEGs, Perturb & Observe. The experimental results show that the tracking efficiency of the proposed MPPT scheme is 99.73% at steady-state compared to the ∼ 90% tracking efficiency achieved by the Perturb & Observe scheme, as well as a 3 times faster dynamic response compared to the fastest method recorded in literature.
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Automotive vehicles with internal combustion engines, such as conventional gasoline and electric hybrid vehicles, exhibit inherent irreversibilities that hinder them from achieving high efficiencies. These irreversibilities manifest... more
Automotive vehicles with internal combustion engines, such as conventional gasoline and electric hybrid vehicles, exhibit inherent irreversibilities that hinder them from achieving high efficiencies. These irreversibilities manifest themselves in the form of thermal losses in the engine and contribute to the total energy consumption in the transportation sector. Waste heat recovery is a method to increase the overall fuel efficiency of vehicles by recovering thermal energy that would be lost from the engine to the environment and converting it to useful energy for the vehicle. In the past years, thermoelectric generators have been intensively investigated for waste heat recovery in vehicles because they are solid-state devices that convert heat directly into electricity and hence have no moving parts, operate quietly, are relatively small, and require low maintenance. This paper presents a review of the literature on waste heat recovery in vehicles through the implementation of thermoelectric generators. First, potential sources or locations in a vehicle for waste heat recovery are presented. Second, the available thermoelectric technology for vehicle applications is reviewed. Then, the components required to create a waste heat recovery system are discussed. The approach for modeling thermoelectric generators to predict the power output is then considered. Finally, experimental investigations by researchers are presented as well as the future trends observed for waste recovery via thermoelectrics.
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Abstract Accurate State of Charge (SOC) estimation is crucial to ensure the safe and reliable operation of Li-ion batteries, which are increasingly being used in Electric Vehicles (EV), grid-tied load-leveling applications as well as... more
Abstract Accurate State of Charge (SOC) estimation is crucial to ensure the safe and reliable operation of Li-ion batteries, which are increasingly being used in Electric Vehicles (EV), grid-tied load-leveling applications as well as manned and unmanned aerial vehicles to name a few applications. In this paper, a novel approach using Deep Feedforward Neural Networks (DNN) is used for battery SOC estimation where battery measurements are directly mapped to SOC. Training data is generated in the lab by applying drive cycle loads at various ambient temperatures to a Li-ion battery so that the battery is exposed to variable dynamics. The DNN's ability to encode the dependencies in time into the network weights and in the process provide accurate estimates of SOC is presented. Moreover, data recorded at ambient temperatures lying between −20 °C and 25 °C are fed into the DNN during training. Once trained, this single DNN is able to estimate SOC at various ambient temperature conditions. The DNN is validated over many different datasets and achieves a Mean Absolute Error (MAE) of 1.10% over a 25 °C dataset as well as an MAE of 2.17% over a −20 °C dataset.