As the automotive market demands improved driving range in electric vehicles (EVs), highly efficient power electronics solutions are a focal point for researchers. Specifically, the low-voltage high-current nature of auxiliary power modules (APMs) with power ratings in the kilowatt range pose a challenge in hindering overall driving range of EVs. Three-port converters (TPCs) enable a highly efficient and power dense means of integrating the DC-DC portion of the on-board charger with the APM in a consolidated solution. To minimize the volume of the three-winding transformer, integrating the TPC, a two-stage APM is assumed in this article in which the second-stage consists of a synchronous buck converter (SBC) capable of 48 V to 9–16 V at 3.6 kW. With a maximum current of 250 A, phase interleaving of the SBC is necessary to improve overall power conversion efficiency. To ensure a sufficient balance of total volume and power loss, a design optimization framework for the SBC is presented in this article. Considerations of parameter variation, device and passive losses, and choice of non-coupled versus coupled inductors are the basis of the developed analytical models used in loss evaluation and inductor design. Results of the framework for 2060 unique designs are presented wherein trade-offs for three optimal designs are discussed yielding the final hardware demonstrator. Experimental results for power conversion efficiency are compared to the analytical model yielding a root mean square error of ~0.24% over the converter operating range.

The advancements in Intelligent Transportation Systems have brought a heightened focus on safety, driven by innovative solutions like Vehicle-to-Everything (V2X) communication, Advanced Driver Assistance Systems(ADAS), and Cooperative Intelligent Transport Systems (C-ITS). Ensuring the safety of vulnerable road users (VRUs) remains a top priority in the transportation sector, and harnessing these cutting-edge technologies offers immense potential to address this concern effectively. This collaborative approach greatly enhances VRUs safety, reduces accidents, and promotes efficient and sustainable mobility. This paper reviews the latest developments in V2X technology, emphasizing its role in improving VRU safety. It explores current V2X standards, use cases on VRU safety, and the evolving research landscape, particularly in trajectory prediction models. These models are critical for foreseeing potential collisions and mitigating V2X-based data transmission delays. Trajectory prediction models can also offer a promising solution to ongoing challenges such as data association, scalability, and bandwidth requirements. By focusing on trajectory prediction, this paper highlights the vital role of predictive analytics in safeguarding vulnerable road users and advancing transportation safety.

Roadside sensors offer a fixed, unobstructed vantage point that can overcome line-of-sight limitations in autonomous driving environments by sharing critical perception data with nearby road agents. While this cooperative approach enhances situational awareness, it also introduces significant computational and communication overhead for autonomous vehicles (AVs). To address this challenge, we propose the Heterogeneous Decision-Aware Attention Graph Transformer (HDAAGT)—a non-autoregressive, encoder-only transformer architecture designed for real-time vehicle trajectory prediction. HDAAGT processes detection data from roadside infrastructure to forecast future vehicle trajectories and communicates these predictions to surrounding agents. By offloading intensive computations from AVs and minimizing transmission latency, our approach improves responsiveness and enables more efficient cooperative perception at intersections and other complex driving scenarios. HDAAGT integrates lane positioning, traffic light states, and vehicle kinematics, enabling a decision-aware graph attention mechanism that models agent-agent and agent-environment interactions. By leveraging a fisheye-based detection and tracking pipeline, our approach eliminates the need for multiple cameras and enables HDAAGT to generate reliable trajectory predictions across the full intersection. We validate our model on the Fisheye-MARC and SinD datasets, demonstrating the capability of HDAAGT in predicting vehicle motion in complex urban intersections with a 1.28 m final displacement error. Additionally, we introduce a new 31k-frame fisheye intersection dataset, the largest of its kind in object tracking, to advance research in intersection-based trajectory prediction.

Back-to-back inverter testing is commonly used to test high-power inverters in laboratory settings. This test involves a second AC/DC converter to feed the AC power back to the DC bus, thereby reducing the demand on the DC power supply to only compensate for system losses. However, this circulating power path presents challenges in zero-sequence current (ZSC) control, particularly when employing space vector pulse width modulation (SVPWM). This necessitates the implementation of an additional control loop. This paper addresses the aforementioned challenge by proposing a coordinated control strategy between the two converters. A detailed system model is developed, and the proposed method is elaborated upon. Furthermore, the paper analyzes the relationship between power factor, modulation index, and fundamental frequency. In comparison with existing methods, the proposed control strategy enables a wide range of power factor and modulation index, while maintaining the modulation strategy of the inverter under test unchanged, thereby improving testing accuracy. The effectiveness of the proposed method is validated using Matlab/Simulink.

Hybrid energy storage system (HESS) consisting of battery and ultracapacitor is a promising solution for range anxiety of battery electric vehicle (BEV) and the life of batteries. In this paper, a comparative study is made on BEV and HESS, considering energy consumption and aging. HESS architecture is selected such that ultracapacitor is connected to the dc bus through a DC-DC converter, so the power flow between battery and the ultracapacitor can be controlled. Control is implemented using a low pass filter, ensuring high-frequency currents are handled by the ultracapacitor and the rest of the currents are handled by the battery, thereby reducing stress on the battery. Performance is evaluated for different drive cycles, and filter cut-off frequency is selected according to drive cycle requirement. The aging model is developed using the Arrhenius equation, and a comparison of the battery state of health (SOH) is done on BEV and HESS models for various drive cycles. It is found that battery in HESS ages slower than that of BEV.

This study investigates the characterization and control of heat exchanger cooling systems by verifying thermal system design correlations combined with numerical simulation methods for electric vehicle (EV) cooling systems. The analyzed cooling system architecture has two powertrain cooling loops isolated from the battery pack to optimize the powertrain cooling system independently. Each loop was analyzed separately, using each component’s heat generation estimates and calculating the required total heat dissipations. Two steps were used to solve the heat transfer in and out of the powertrain cooling loops. First by calculating the heat transfer area to determine the type of heat exchanger required to dissipate the heat. Second, after selecting a water-water (W-W) heat exchanger, the coolant temperature out of the heat exchanger and machines were calculated. These calculations were modeled in a numerical simulation which combines both steps mentioned. Testing was performed on the heat exchanger to characterize its thermal performance including its overall heat transfer coefficient at different flow rates and temperature differences. The vehicle thermal system model was tested using UDDS, HWFET, and US06 drive cycles to understand thermal generation in the powertrain. As speed varied within the drive cycles of the numerical simulation, the heat exchanger and control strategy from the pump kept the temperatures below the predicted maximum limits by approximately 20 °C for both powertrain cooling loops.

The dual active bridge (DAB) converter is a popular candidate for DC-DC converter applications in industrial and automotive applications. While single phase shift (SPS) control is the conventional control technique for DAB converters, different phase shift control techniques have been proposed with multiple control variables. Extended phase shift (EPS) control is one such control technique with an extra degree of freedom to minimize the backflow power (BFP) and inductor peak current, which claims to be superior to SPS control. In this analysis, functions for BFP and peak current in SPS and EPS control for both buck and boost operations, considering all possible cases of the inductor current waveform are derived. The two control variables of EPS control are reduced to a single control variable to minimize BFP and peak current. To identify the most efficient control technique between SPS and EPS control, efficiency analysis is carried out over a wide voltage and load range.

The inherent high nonlinearity of Switched Reluctance Machines (SRMs) poses significant challenges to modeling. Conventionally, large-data-size lookup tables (LUTs) are used, which consume extensive storage space in digital signal processors (DSPs) and complicate the application of well-established PI control techniques. This paper presents a linear flux SRM model, leveraging the space mapping method to map the SRM's nonlinear flux profile into a linear space in relation to both current and position. The proposed linear model offers two key advantages. First, it reduces data storage needs due to smaller LUTs. Second, it enhances the feasibility of applying PI control. Simulation results of an 8/6 SRM are presented to illustrate the proposed approach.

This work is a study of the current state of vehicle trajectory analysis in intersections monitored by a single fisheye camera. The challenges related to using fisheye cameras at intersections are explained, and a zone definition-based framework to detect illegal maneuvers is introduced for busy intersections containing noisy detection and tracking data. The methodology is developed by conducting data rectification, distance-based data filtering, and trajectory classification, followed by detecting banned maneuvers. The illegal maneuver detection algorithm is further extended for defining different banned maneuvers, including illegal turns and box-blocking contravention at intersections. Lastly, the proposed framework is implemented in real-world data captured from the Cubic’s GRIDSMART bell camera, and the results are explained in detail.

Synchronous optimal pulse-width modulation (SOPWM) is an effective solution to reduce switching frequency without increasing the current distortion. This method is widely used along with stator flux tracking in traction applications of induction motors. However, stator flux tacking is not an ideal control technique for permanent magnet synchronous motors (PMSMs). This paper studies SOPWM with stator current tracking for PMSM traction applications. Stator current tracking with SOPWM suffers poor steady-state performance when the PMSM operates around discontinuity of the switching angles due to the voltage disturbance generated from current harmonics. This problem is usually solved by using continuous switching angles. However, this approach brings more overall current distortion due to sub-optimal switching angles. To address this issue, a novel hysteresis control-based SOPWM scheme with continuous switching angles is proposed. Preliminary simulation results indicate that the proposed method can offer low current distortion compared to conventional and continuous SOPWMs.

The vibration/noise and torque ripple are two inherent issues for switched reluctance motors (SRMs), one of the effective methods to address these two issues is flattening both the total radial force and total torque. In this paper, an optimized quadratic-sharing-function-based radial force and torque simultaneous flattening method is proposed for SRMs. Firstly, the features of the radial force and torque characteristics are analyzed without considering saturation. Then, with these unique and specific features, four regions are defined to develop the simultaneous radial force and torque control method based on the linear sharing functions. To incorporate the saturation effects in the proposed method, the quadratic sharing functions are adopted. The proper parameters of the quadratic sharing functions and the region definition at different operating conditions are obtained through the genetic algorithm (GA) optimization. The switching angles and reference current of the conventional current chopping control (CCC) method are also optimized by GA for fair comparison purpose. Extensive simulation results are presented in this paper, and these results prove the effectiveness and superiority of the proposed method regarding the simultaneous radial force and torque control.

System reliability and design optimization are the main concerns in power electronic converters of more-electric aircraft (MEA). The dual active bridge (DAB) is the topology usually considered to link the HVDC bus to the LV network onboard the aircraft. This paper proposes a design and control algorithm that maximizes the power transmission efficiency by minimizing the transformer RMS current while considering the converter parasitic elements in the process. The optimization methodology includes two layers of optimization through a genetic algorithm (GA); optimization of transformer turns ratio and DAB inductor and phase angle optimization by using triple phase shift (TPS) control mode. The high-turn ratio of the isolating transformer utilized in this application results in a considerable effect on the converter performance. The parasitics effect is discussed and FEA simulations are carried out in Ansys Q3D from which the stray inductances are extracted and fed to the optimization algorithm.

Reliability, efficiency, and control optimization are the key features of modernized aircraft. This paper proposes a control algorithm across various voltages and load conditions that maximizes the power transmission efficiency between the high voltage DC (HVDC) link and the low voltage (LV) network aboard the aircraft. The algorithm is developed for a Gallium Nitride (GaN)-based dual active bridge (DAB) converter, for more electric aircraft (MEA). GaN is considered for maximized efficiency, weight reduction and improved thermal performance. The dual phase shift (DPS) and extended phase shift (EPS) modulation techniques are optimized using Genetic Algorithm (GA) and verified through simulation. The optimization algorithm aims at minimizing the backflow power, peak current, and converter losses. Efficiency results of the DAB converter are presented and compared under different modulation techniques. The results are validated on a 4 kW GaN-Silicon (Si) DAB converter.

The operating voltage of powertrains in Battery Electric Vehicles (BEVs) has witnessed an upward trend due to advantages in ultra-fast charging and reduction in run-time losses due to lower operating currents in the powertrain. Original Equipment Manufacturers (OEMs) such as Porsche, Audi, and Lucid Motors have introduced vehicles with powertrains operating from 800 V to 924 V. Due to increased switching losses at these voltage levels, the operation of DC-DC converters requires cascading of existing topologies or a multi-level operation. With increasing battery sizes, traditional Level-2 3.3 kW on-board chargers (OBCs) are deemed insufficient to fully complete a charge overnight. Thus, due to increasing voltage and power levels in commercial BEVs, this paper investigates the Grid to Vehicle (G2V) mode’s priority operating regions for a 11.5 kW Level-2 on-board charger in context of an 800 V powertrain. A design procedure for three potential DC-DC converter configurations is performed, and an optimization process is established. A multi-domain comparison highlighting the cost, advantages, and disadvantages of each configuration has been presented.

Employment of Silicon Carbide (SiC) devices and the use of multiphase drives are two emerging trends in electric vehicle (EV) applications. However, technology assessment combining both trends for traction applications has not been thoroughly examined yet. This paper presents a quantitative and qualitative analysis to examine the feasibility of SiC-based multiphase traction inverters. Specifically, voltage source inverters (VSI) and nine switch inverters (NSI) with different phases (five-, six-, and nine-phase) are evaluated in terms of device count, dc-capacitor sizing, efficiency, power density, and cost. The multiphase inverters in the case study are rated at 100 kW considering 400 V and 800 V EV powertrains. Compared to the conventional three-phase VSI, the six-phase VSI was found to have the best feasibility. The latter enjoys reduced dc-capacitor requirements, lower ac cabling cost, and higher fault tolerance capability, while maintaining the same efficiency and power device count.

This paper reviews zero-voltage switching (ZVS) possibilities with multiple phase shift modulations for the more electric aircraft (MEA). Three additional triple-phase shift modes are proposed and analyzed in detail based on ZVS conditions beyond the traditional six modes. A minimum peak current stress closed-loop hybrid multiple phase shift (HMPS) modulation scheme based on the proposed modes of operation is presented. Multiple phase shift angles are optimized based on accurate pre-calculation of output current, providing the minimum peak current and decreasing the switching loss, enabling the design of power-dense converters. The proposed HMPS modulation shows higher efficiency at light load and boundary operating points than the existing SPS and unified TPS (UTPS) methods. Finally, a 10kW SiC DAB converter hardware setup for the MEA application is implemented. The efficiency of the setup is up to 96.5%. At boundary operating points, the converter obtains a peak efficiency of 94.7% with the proposed HMPS method. The converter shows peak efficiency improvements of 1%-2% compared to traditional modulation.

A simplified space-vector pulse width modulation based overmodulation technique for permanent magnet synchronous motor drive system is proposed. There are two overmodulation modes in the proposed method. The duties of two modes for overmodulation region in modulation hexagon sector one are generated by simplified linear formulae. With simplified linear duty generating formulae, the computational burden is relatively smaller than conventional overmodulation method. DC bus voltage is maximum utilized and modulation index can be extended to the maximum value. The transition between linear modulation and overmodulation, and overmodulation and six-step operation is smooth. The results of verification on a PMSM platform demonstrate the effectiveness of the proposed method.

This paper presents an efficiency evaluation of two six-phase inverter topologies for automotive applications: voltage source inverter (VSI) and nine-switch inverter (NSI). Their efficiency is studied for electric powertrains rated at 400 V and 800 V, and using silicon carbide (SiC) MOSFETs rated at 650 V and 1200 V operating at a switching frequency of 30 kHz. Prior to efficiency evaluation, a thorough analysis on the total device count required for 100 kW design is investigated for both topologies. It is found that NSI enjoys a superior efficiency when compared to six-phase VSI, at the expense of increased total device count.

This paper introduces an improved real-time Model Predictive Climate Control (MPCC) technique to reduce power consumption in Heating, Ventilation and Air Conditioning (HVAC) system of the Battery Electric Vehicles (BEVs). In the presented control technique, the fan, heating and cooling power usage is optimized considering the effect of the ambient temperature. Moreover, the need of a physical temperature measurement sensor is eliminated using an ambient temperature observer. In a typical BEV, the HVAC load is significant and it influences the overall vehicle performance and driving range. Therefore, a real-time control system capable of maintaining desired cabin temperature while achieving maximum HVAC efficiency is highly desirable. In the proposed MPCC, the optimum split of the battery power between the heating\cooling and the fan power is identified as a function of ambient temperature through an offline optimization process and used in the form of a lookup-table for real-time implementation. It is demonstrated that the proposed MPCC improves energy consumption efficiency of the entire HVAC system up to 5% by dynamically adapting to the variations in the ambient temperature. Furthermore, owing to the online temperature observation process, the proposed HVAC control system allows elimination of ambient temperature sensor and corresponding maintenance efforts. In this paper, the performance of the proposed MPCC is evaluated over a single-zone HVAC model of a BEV in MATLAB\Simulink®environment.

This paper analyzes the operation of mutually coupled switched reluctance machines (MCSRMs) at generating mode with sinusoidal current excitation. The sinusoidal current excitation for MCSRMs enables the use of the standard voltage source inverter and the conventional modulation methods such as the space vector modulation. When the MCSRM operates at generating mode, there are infinite number of operating points that can output the same average torque. The differences between those operating points are the corresponding torque ripple, efficiency, and power factor. Thus, the influence of these three factors on the operation of the MCSRM are investigated. Since MCSRMs has no field excitation source, the phase windings of the machine are magnetized from an external source. The amount of the reactive power consumed depends on the direct-and quadrature- axis currents. This means for the same average torque applied on machine shaft, the amount of reactive power can be minimized. A 2kW 12/8 MCSRM is used in the study. The analysis is conducted using FEA and MATLAB.

This paper presents a novel self-commissioning procedure for the identification of inverter nonlinearity constant comprised of the average voltage drops on switches and diodes in conduction state and switching delays. Simultaneous estimation of phase resistance, d-axis synchronous inductance, and inverter nonlinearity constant is achieved at standstill condition by injecting sinusoidal d-axis current. The advantages of the proposed self-commissioning method are twofold: 1) The co-estimation capability provides insensitivity towards errors in resistance and d-axis inductance. 2) While sinusoidal d-axis current is injected, the q-axis current is actively maintained at 0A. Thus, no torque is generated during the self-commissioning period. The effect of discontinuous distortions due to non-ideal switching as well as current sensor noise is rejected by limiting the estimation period within a feasible estimation window. Thereby, a necessary minimum phase current magnitude is established for achieving accurate estimation. This paper also provides parameter convergence analysis and the existence of unique solutions during proposed self-commissioning process, further justifying the choice of proposed feasible estimation region.

This paper studies the electromagnetic interference (EMI) noise modeling for a three-level active neutral point clamped inverter. Although time-domain detailed modeling leads to more accurate results, frequency-domain modeling techniques are commonly used as a faster prediction method. Compared with the conventional differential mode (DM) EMI modeling of power inverters that use only one current source, it is shown that two current sources are required for more precise modeling. A new unified model is proposed for an active neutral point clamped inverter based on the existing equivalent circuit models for common mode (CM) EMI and the developed DM model. Both CM and DM EMI emissions are predicted by the proposed model and compared with the time-domain results. Simulation results indicate that the modeling precision is improved by 56%.

This paper presents a closed-form formulation to model the switching loss in single-phase dual active bridge converters (DAB). The proposed model is general and covers all modulation techniques with one, two, or three control parameters. Moreover, in this paper, the switching loss is minimized in a DAB converter controlled by the extended phase shift modulation (EPS) utilizing the model. In other words, the proposed loss model is used in a standard nonlinear optimization approach targeting the switching loss. By this optimization, the efficiency of the DAB converter is improved notably. Particularly, in IGBT-based converters with high switching loss, the optimization approach reveals significant improvement. In the designed 10kW DAB converter controlled by EPS modulation with optimal parameters, the switching loss is reduced by 22% compared to the traditional single-phase shift modulation (SPS). The total efficiency is increased by 0.6%, employing the proposed model and the optimization process.

This paper analyzes permanent magnet synchronous machines (PMSM) under open phase and phase-to-phase fault conditions within an electric vertical take-off and landing (eVTOL) aircraft. The development of a detailed mathematical model for a PMSM under the open phase fault (OPF) and phaseto-phase short circuit fault (P2PSCF) conditions are presented and implemented in MATLAB/Simulink along with its results within a ring bus electrical distribution system (REDS) for an eVTOL is presented. The behavior of both faults is investigated. Fault-tolerant control (FTC) is applied during the post-fault operation, and the copper losses and torque ripple are analyzed. Two fault mitigation techniques, 1) disabling the inverter (FTC1) and 2) creating a virtual neutral point (FTC2) with the inverter, are introduced for the P2PSCF. FTC1 had a peak-to-peak torque ripple of 309Nm with 1.55kW reduction of copper losses. FTC2 was found to respond faster than FTC1 and generated 157Nm peak-to-peak torque ripple. The OPF FTC was analyzed where only current references are changed for the same PI controller structure to enable a fail-operational state for the eVTOL. The OPF FTC achieved 348Nm peak to peak torque ripple compared to 371Nm to pre-fault conditions.

This paper proposes an adaptive voltage regulation (VR) flux-weakening (FW) control technique for dual three-phase (DTP) permanent magnet synchronous machine (PMSM) drives. Firstly, a small-signal model is developed to demonstrate the need of gain adaptation in order to maintain the controller bandwidth. Moreover, the small-signal model serves as a tuning tool for the FW proportional-integral (PI) controller. Then, the proposed adaptive controller is implemented and tested on a 100 kW DTP-PMSM drive. Simulation results demonstrate an improved drive performance at high speeds when benchmarked against non-adaptive controllers. Furthermore, the adaptive controller offers an extended speed range.

In this paper, a new method to reduce the steady state torque tracking error of finite control set model predictive torque control for switched reluctance motor drives is proposed. The steady state tracking error is considered as one of the main shortcomings of the conventional Finite Control Set Model Predictive Control (FCS-MPC). This can happen due to parameter uncertainties or when the multiple objectives are achieved by a single function with weighting factors. In the conventional model predictive torque control for SRM, the control action is obtained by a multi-objective cost function designed to track a reference torque while minimizing the phase currents over the prediction horizon. The optimal switching state which minimizes the cost function is selected and applied at each switching instant, which results in the steady state torque tracking error. In this paper, a compensation term is added to the reference torque at each sample instant to minimize the torque tracking error. The compensation term is calculated based on the estimated average torque tracking error in the previous sample times. Simulations on a three phase, 12/8, 2.3 kW SRM show promising results with the proposed method as compared to the conventional FCS-MPC.

This paper presents a detailed PCB design for a 70kW 3-level Active Neutral Point Clamped traction inverter. The proposed design is focused on stray inductance reduction and thermal performance optimization. The voltage overshoot and maximum allowable stray inductance of the busbar are investigated in detail. Current density and its effect on the PCB temperature are analyzed using 3D finite element analysis.

This paper introduces a design methodology for a Switched Reluctance Motor (SRM) for an 80 kW Battery Electric Vehicle (BEV) propulsion application. The methodology aims to satisfy the high power density requirement targeted for an electric motor for a BEV application, while maintaining improved efficiency and torque quality. Iterative modeling effort has been employed for the design, including finite element analysis for the electromagnetic characteristics of the motor and dynamic modeling for performance analyses. The design approach starts with determining the motor geometry followed by sensitivity analysis for the motor performance considering various motor parameters. Then the SRM conduction angles are optimized with multi-objective genetic algorithm to improve the torque density and reduce torque ripple. The performance is further analyzed and compared to the target motor.

An adaptive gain for voltage controller in fluxweakening control of permanent magnet synchronous motor (PMSM) is proposed. Based on voltage angle control scheme, voltage feedback controller can adjust control current locus and utilize the DC link voltage in flux-weakening region. The voltage controller is controlled using the difference between voltage reference magnitude and and a proper inverter limit value. The analysis of voltage controller is carried out, taking into account of modulation delay to issue the compensation performance with different voltage feedback gains from difference PMSM operating conditions. The adaptive gain of voltage controller is applied with forward feedback voltages and current vector to improve dynamic response with smaller voltage errors. The results of verification on a 7-kW PMSM platform demonstrate the effectiveness of the proposed method.

In this paper, the effect of the parasitic resistance on the operation of the dual active bridge (DAB) converter is investigated. Analytical equations of the input-output voltage characteristic for the single phase shift (SPS) and the triangular current (TC) modulation techniques, that consider the parasitic resistance on the secondary side, are proposed. The new equations are verified through simulations in Matlab/Simulink. In both SPS and TC modulations, the power transmission capability is reduced due to the parasitic resistance. Moreover, with SPS modulation, the maximum output voltage is obtained at different operating points if the parasitic resistance is neglected or not. On the other hand, the voltage characteristic has a similar trend with the TC modulation. Therefore, the control of the DAB needs to be adjusted to consider the parasitic components.

Path planning is discussed in this article for an autonomous vehicle given a route to follow. Route data is considered to be available for a distance ahead of the vehicle in a receding horizon manner. Linear approximation of the nonlinear equations for a vehicle following a path is obtained. Based on these equations, the optimization problem is formed in a convex optimization format and solved to find the optimal path. Optimality is a trade-off between comfort and travel time. Results are provided for some cases considering that the vehicle is traveling in the Suzuka circuit and the observable horizon ahead of the vehicle is a part of this track. Results are discussed for a few trade-off values and analyzed from the practical point of view, which shows that the method is capable of producing an optimal path to follow in an insignificant amount of time. Finally, an alternative approach for improving model accuracy is proposed and discussed. Finally, it has been concluded that the proposed method has a significant potential for motion planning/controlling applications for an autonomous vehicle using model predictive control.

This paper presents an online adaptive method to adjust the phase turn-off angle in finite control set model predictive control (FCS-MPC) of switched reluctance motor (SRM) drives to reduce the negative torque production. The current in the inductance falling region generates negative torque which increases the torque ripple, RMS current, and reduces the efficiency, especially at high speed operation. The existing FCS-MPC needs long prediction horizon to predict and reduce the negative torque production by adjusting the turn-off angle. However, long prediction horizon substantially increases the computational burden. This paper proposes a simple online method to automatically adjust the phase turn-off angle for single prediction horizon FCS-MPC. The proposed method is validated in simulations for a three phase, 12/8, 2.3 kW SRM in the entire operating region. The comparison with the existing MPC shows the effectiveness of the proposed method in terms of efficiency and torque ripple reduction.

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).

In this paper, a new state of charge (SOC) estimation method is proposed combining Long Short-Term Memory Network (LSTMN) battery model and Kalman filter (KF) considering temperature dependency. The technique has been compared to the equivalent circuit model (ECM) and the combined model (CM) using dynamic stress test data. A KF is applied to each model to realize the dynamic estimation of battery states. Based on the collected data from the federal urban driving schedule, terminal voltage approximation and SOC estimation are carried out, and the results are compared among the models. This paper includes the following contributions: (1). A LSTMN battery model that shows stronger robustness against temperature is implemented. (2). A LSTMN-KF method is proposed for SOC estimation at different temperatures and is compared with ECM-KF method and CM-KF method. (3). The proposed method eliminates the need for SOC-OCV lookup table and does not rely on the chemical characteristics of batteries.

The paper presents an observer assisted current reconstruction based method to estimate the three phase currents by utilizing only one dc-link current sensor to realize position sensorless control of interior permanent magnet synchronous machine (IPMSM). The current reconstruction technique needs dc-link current information for at least two vector transition regions in a switching period to estimate the three phase currents. However, it is challenging at the sector boundary regions (immeasurable region) without shifting the space vectors of the pulse width modulation (PWM). In the proposed method, the current estimation is assured in the boundary region without shifting the PWM vectors with the help of assistive model-based observer. The assistive model-based observer is a Luenberger type observer that estimates the back electromotive force (EMF) based on the error between the reconstructed and estimated currents. An adaptive band-pass filter is applied to the estimated back EMF to eliminate the undesirable harmonics in the immeasurable region. The proposed scheme feedbacks the estimated current to the current controller and utilizes the estimated back EMF to estimate the position and speed. The algorithm is implemented in dSpace platform and validated by experiments.

Finite Control Set Model Predictive Control (FCSMPC) is widely acknowledged as a simple and effective control scheme for permanent magnet synchronous motor (PMSM) drives. It delivers the merit of quick dynamic response however faces problems such as large current ripples and unsatisfactory steady state performance. This paper proposes a FCSMPC method which minimizes the current ripples by integrating the concept of duty cycle and virtual voltage vectors. In the proposed method, six symmetrically positioned virtual voltage vectors are introduced in addition to the six original active voltage vectors to expand the finite control set, among which one optimal vector is selected and applied in each sampling interval according to the enumeration-based principle of cost function minimization. Then, the duration of the optimal vector is decided by an efficiently calculated duty ratio. Compared to the conventional FCSMPC, the proposed method causes no additional computation burden but exhibits much lower current ripples. The proposed method is experimentally compared with two typical FCSMPC methods for an interior permanent magnet synchronous machine and it is proved that the proposed method delivers better steady-state performance while maintaining quick dynamic response.

This paper presents the design of an external-rotor switched reluctance motor (SRM)for a direct-drive washing machine application and a comparison with a commercial model. First, a complete review of the state-of-the-art for “washing appliances” has been discussed and design requirements have been analyzed. Secondly, an external-rotor SRM with high number of poles has been chosen to obtain high torque density and power density. Then both, the electromagnetic and thermal performance of the external SRM have been evaluated by finite element analysis (FEA)in wash mode and spin cycle mode operations to confirm that the design fully satisfies the specifications at low and high-power range with high reliability. The mechanical prototype of the SRM has also been provided, which uses the same housing as the commercial benchmark model. Finally, the SRM design for the washing machine application has been validated based on experimental results.

This paper proposes a simplified convex optimization-based sensorless scheme for interior permanent magnet synchronous motor (IPMSM)drives. The computational burden of the existing convex optimization-based method is significantly reduced by a single variable cost function, which is based on the machine voltage equations in the stationary reference frame. With less computation, the proposed method provides good performance characteristics similar to the existing one, e.g., dynamic speed response and smooth transition between the low and high-speed ranges. The convergence capability of the cost function is also confirmed by a convexity analysis. The feasibility of the control technique is experimentally validated in a test bench, demonstrating the accuracy of the technique and its reduced computational burden.

In three-phase dual-active-bridge (DAB) converter, the zero-voltage-switching (ZVS) range, DC capacitor ripple current and converter efficiency are significantly impacted by the selectable system parameters, including transformer turn ratio n, switching frequency f and leakage inductance Lk. The converter performance also varies with different operation conditions, i.e., input voltage, output voltage and output power level. Therefore, these parameters need to be carefully selected to achieve optimized performances. In this paper, a comprehensive study of the parameter selection for the three-phase DAB converter is conducted under different operation conditions. A new parameter fL is defined to reduce the analysis from 3 dimensions to 2 dimensions, which simplifies the analysis of transformer turn ratio significantly. Furthermore, the effective operating area (EOA) of f and Lkare defined for feasible transformer designs. The current stress of switches and DC capacitors are studied in the EOA to help determine the range of f and Lk. Finally, the converter total loss and efficiency are analyzed at full and half load with different input and output voltages. The converter parameter (n, f, Lk) can be selected using ZVS and efficiency criteria. The tradeoff between high efficiency, wide ZVS area and low capacitor ripple current can be achieved accordingly.

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 capacitors' life. In this paper, the design procedure of the hybrid capacitor bank for the single-phase inverter with unipolar modulation will be discussed. The simulation and experimental results will be provided to verify the design of the hybrid capacitor bank for a 3kW single-phase PV inverter.

In most mechanical and electrical systems, reliability is paramount. Consumers, users and operators trust that their product will perform properly over its expected lifetime. Electric Vehicles (EVs) and Hybrid-Electric Vehicles (HEVs) are no exception to this statement. One of the most important components to consider when determining the reliability of EVs and HEVs is the electric motor. Within electric motors, many things can cause reduced reliability. This paper will focus on the most important component: the bearings. In this review paper, a general summary of bearing failure methods is provided along with an in-depth analysis of all facets relating to the shaft voltage and bearing current phenomenon with specific discussion relating to EV and HEV motors. Subsequently, this paper will provide a review of several mitigation techniques to render the bearing current failure mode obsolete.

This paper presents the low speed position estimation scheme for an IPM machine controlled by model predictive control with finite control set. The career signal injection is not viable as there is no PWM to superimpose it with PWM for this type of control. The pulse vector injection technique requires current derivative sensors which makes the overall scheme less attractive. This paper utilizes the inherent high frequency vector injection of the model predictive control to extract the position information. It is shown that the high frequency current response is amplitude modulated with respect to the position. A demodulation technique based on the reactive power estimation is proposed. The simulation results at various initial positions confirm the validity of the proposed position estimation scheme.

A battery-ultracapacitor Hybrid Energy Storage System (HESS) combines the advantages of both Li-ion batteries and ultracapacitors. Li-ion batteries sustain a relatively long electric only driving range but degrade if exposed to high C-rates and large number of cycles. Ultracapacitors are robust, have a quasi infinite cycle life and can sustain highly dynamic power profiles. This paper proposes a HESS Linear Quadratic Regulator (LQR) design to mitigate issues related to battery wear and peak power demands for electric and hybrid electric vehicles. The LQR controller imposes the battery current with a bidirectional power electronic converter that interfaces the battery to the ultracapacitor. The HESS is accurately modeled using experimental battery and ultracapacitor data in conjunction with equivalent circuit models. Simulations are carried out to validate the LQR controller on a UDDS drive cycle. Reduced battery wear is quantified using a spectral analysis of the battery current, which identifies microcycles.

Electric vehicle battery modeling and state-of-charge prediction has gained a lot of importance with the growing range anxiety among electric vehicle users. The future of battery implementation in electric vehicles might be in their customized design according to specific journey conditions. As such, this paper highlights the application of a novel concept — Journey Mapping for a Ford Focus Electric 2012's battery characterization and SOC prediction with the help of Genetic Algorithm and the Recursive Least Squares techniques respectively. The Journey Mapping concept, which re-defines driving cycles in order to better capture the journey of a vehicle by including various external conditions such as weather, terrain, traffic, driver behavior, road, aerodynamic and vehicle proved to be a a more accurate testing bed for electric vehicle battery modeling.

Online estimation of losses is important to improve control, operation and monitoring of electrical machines. This paper focuses on investigation of iron losses using a magnetic circuit model for its accuracy and adaptability to online estimation purposes. A customized magnetic circuit of an IPM machine is proposed that captures slotting, non linearity, cross saturation and localized effect of flux bridges. A technique is presented to compute the alternating stator and rotor flux from the static magnetic circuit. The required computations are reduced introducing pseudo mmf sources that avoid solving magnetic circuit at several rotational steps. The stator and rotor core losses are found corresponding to each harmonic component of alternating flux density. The results are validated with Finite Element analysis with good correlation.

Thermoelectric Generators (TEG) can harvest a part of the thermal energy otherwise lost in the exhaust gases of vehicles and are combined with Maximum Power Point Tracking (MPPT) schemes to maximize the power output. This paper proposes a novel TEG MPPT scheme named High Frequency Injection (HFI) method. The method injects a high frequency voltage to the TEG and yields a power with a high frequency component. This component is demodulated and yields a signal proportional to the distance from the optimal operation point. The duty cycle setpoint is adjusted with a proportional-integral (PI) controller. The method is compared to the Perturb & Observe method using a drive cycle. Both show good results in terms of dynamic tracking of the optimal operation point. However, the HFI method is shown to be significantly more robust against sensor noise.

This paper proposes a novel initial rotor position estimation algorithm for Interior Permanent Magnet Synchronous Machine (IPMSM) drives. First, the rotor position is determined based on the machine saliency using the flux equations in the stationary reference frame. Since the machine saliency performs two periods in one electrical cycle, there exists an ambiguity of 180° in the estimation result. The location of the magnetic north pole is detected using a generalized polarity detection method. This method injects voltage pulses and compares the current response with the expected response using the d-axis differential inductance profile. An accurate nonlinear machine model is introduced for analysis and simulation of sensorless control in IPMSM drives. The model uses the machine flux as dynamic equation and the flux current relationship as output function avoiding approximations due to saturation. The initial position detection procedure is validated with this model using experimental current-flux data.

This paper investigates the effect of regenerative braking on the overall energy consumption of an electric taxiing system which is integrated in the main landing gear of a single aisle midsize aircraft. In the evaluated system, electric motors are responsible for the aircrafts propulsion while taxiing on ground. First, the system is modeled and analyzed in order to design an electrified traction system for the taxiing of the aircraft. The followed method to design the electric taxiing powertrain system is presented. Based on the aircraft's mass and the interaction between the wheels and the tarmac, a simulation model is developed for the electric taxiing system. This model is simulated over a real taxiing takeoff drive cycle to evaluate and characterize the energy and power requirements of the traction system. Moreover, the power and energy rating of the traction system (electric motors, power electronics and battery capacity) are determined by the consideration of the specific taxing scenario and evaluated drive-cycle. The assumptions and model used to size the powertrain especially the electric motors are confirmed by the simulation results. Furthermore, the results of the considered drive cycle show that regenerative braking can potentially enable a reduction in the overall tractive energy up to more than 8%.

This paper presents a phase shifted full bridge (PSFB) DC/DC converter with current doubler synchronous rectifier for auxiliary power units (APU). The proposed converter is suitable for low output voltage with high output current applications like APU. A zero current switching (ZCS) control scheme is proposed to reduce MOSFET body diode conduction loss of synchronous rectifier. The proposed control scheme is verified by experimental results with a 1200W, 100 kHz prototype.

This paper presents a comprehensive methodology for topology evaluation of bidirectional boost converters in electrified vehicle applications for higher power density. Based on the given specifications, major components in the converters are designed and sized, including the boost inductor, power module, and DC-link capacitor. 3D Finite Element Analysis (FEA) simulations are conducted to evaluate the inductor loss. Power module loss is estimated based on the manufacturer datasheet parameters. With the proposed evaluation methodology, four bidirectional boost converter topologies are compared in terms of efficiency and power density: Single Phase Single Inductor (SPSI), Dual Phase Single Inductor (DPSI), Dual Phase Dual Inductor (DPDI), and Dual Phase Coupled Inductor (DPCI). The comparison results show that the power efficiency of DPCI is highest among these topologies, and DPCI can reduce the size of the inductor and DC-link capacitor. Therefore, DPCI is a strong candidate for bidirectional boost converter in electrified vehicle applications.

As a cost-effective, healthy, and environmentally friendly personal mode of transportation, electric bicycles (E-bikes) are gaining an increasing market share from conventional bicycles and automobiles in urban communities. At the same time, the simple structure, high torque and power density, as well as low cost of switched reluctance machines (SRM) make them a strong candidate for E-bikes. This paper presents a 3-phase, external-rotor SRM with 6 stator poles and 10 rotor poles (6–10), designed for an E-bike application. The SRM design and simulation is initiated by evaluation of the bicycle kinematics. Analytic estimates are used to determine machine main dimensions and output power equation, followed by comprehensive finite element analysis (FEA). A torque ripple reduction control is presented and detailed thermal analysis conducted to improve the design.

An energy management system is proposed for a grid-connected microgrid with on-site battery storage and renewable energy sources. The system controls power flow between the microgrid and grid in order to effectively utilize renewable energy and maximize economic benefits for the customer and the utility operator. The power flow is optimized by formulating and solving a mixed-integer-linear-program optimization over a rolling horizon window. Multiple objectives concerning economic benefits, cost of battery operation and grid power profile shaping are built into the optimization. So called battery incremental red-zone power rates are among unique battery management features of this formulation. Careful consideration is also given to reducing the computations so the controller can run on an embedded computer in real time. Simulation results highlight the effectiveness of various novel aspects of the proposed controller.

This paper discusses the need for modeling and simulation of electric and hybrid vehicles. Different modeling methods such as physics-based Resistive Companion Form technique and Bond Graph method are presented with powertrain component and system modeling examples. The modeling and simulation capabilities of existing tools such as Powertrain System Analysis Toolkit (PSAT), ADvanced VehIcle SimulatOR (ADVISOR), PSIM, and Virtual Test Bed are demonstrated through application examples. Since power electronics is indispensable in hybrid vehicles, the issue of numerical oscillations in dynamic simulations involving power electronics is briefly addressed.