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This paper presents an integrated control strategy for a starter/generator (S/G) system based on five-phase dual-stator winding induction machine (FPDWIM). The FPDWIM has a cage-type rotor and two sets of stator windings. One is a five-phase control winding (CW), and the other is a five-phase power winding (PW). In the starting mode, the FPDWIM works as a motor. The CW provides both active power and reactive power to drive the engine. In the generating mode, the CW mainly handles reactive power while the PW outputs active power. To achieve the integration of the starting and generating controls, indirect CW-flux-oriented control (ICWFOC) to operate in both starting and generating modes is proposed in this paper. In starting mode, the CW current and flux are controlled to output a constant starting torque; while in the generating mode, both CW and PW dc bus voltages are regulated. In this way, the principles and structures of the control strategies in both modes are compatible, resulting in a simpler implementation and improved performance. With the proposed control strategy, the system can complete the starting–generating operation with a smoother transition process. Simulation and experimental results are compared to validate the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method for detection and isolation of wastegate (WG) faults in a turbocharged (TC) gasoline engine. This paper starts with a fault effect analysis on the WG faults, including WG stuck open and stuck closed, which is an early step in a detection strategy design. Then, a second-order sliding-mode observer (SOSMO) is proposed to capture the exhaust manifold dynamics. The observer uses experimentally validated engine models to estimate the WG position and a virtual force. The virtual force represents the external disturbances that disrupt the WG operation and enables the proposed SOSMO to estimate the WG position robust to the faults. Using this force, a detection and isolation algorithm is presented and experimentally verified on a modern TC gasoline engine. Test bench results show that the proposed strategy can successfully detect and isolate the two different WG faults. [ABSTRACT FROM PUBLISHER]

The paper describes application of unmanned robot applied to automotive test (URAT) to save time, costs, and to improve accuracy of tests. A hierarchical coordinated control method based on fuzzy logic theory is proposed for URAT, to realize the coordinated control and the accurate speed tracking of driving test cycle during all kinds of conditions. The system structure is briefly described in the paper. Similar to a skilled human driver, a control method based on Saridis hierarchical architecture to coordinate multiple robot manipulators systems for the automotive test system is presented. The coordinated movements for throttle mechanical leg, clutch mechanical leg, brake mechanical leg are designed. On top of that, the fuzzy speed controller for URAT is used to accurately track the desired vehicle velocity under different test conditions. Experiments have been conducted by using a Ford FOCUS car. The proposed control method of URAT is experimentally proved and compared with other control methods and with human driver performances. [ABSTRACT FROM PUBLISHER]

This paper presents an overview of technology related to on-board microgrids for the more electric aircraft. All aircraft use an isolated system, where security of supply and power density represents the main requirements. Different distribution systems (ac and dc) and voltage levels coexist, and power converters have the central role in connecting them with high reliability and high power density. Ensuring the safety of supply with a limited redundancy is one of the targets of the system design since it allows increasing the power density. This main challenge is often tackled with proper load management and advanced control strategies, as highlighted in this paper. [ABSTRACT FROM AUTHOR]

This paper proposes an integrated method of three-phase ac excitation and high-frequency voltage signal injection (HFVSI) for sensorless controlled starting of brushless synchronous machines (BSM) used as starter/generator in variable frequency ac power systems of civil aircraft. Fixed 400 Hz of the three-phase ac power is adopted both for the ac excitation and HFVSI in the initial starting process to eliminate the bulky rotor position sensor for BSM. The resulting 6th sequence harmonic voltage determined by the rotating rectifier is utilized as the HFVSI into the field-winding of main generator without any extra high-frequency signal injection. The rotor position is estimated by the high-frequency response signals extracted from the armature windings of main generator. Due to the nonlinear rotating rectifier linked in the HFSI chain, a novel frequency-insensitive asynchronous demodulation strategy is proposed in this paper for rotor position estimation. Furthermore, the initial rotor position detection is calibrated by polarity decision of the induced currents of the armature windings within the establishment procedure of field current of the main generator at standstill. The effectiveness of the ac excitation and feasibility of rotor position estimation for sensorless starting control of BSM are validated by the simulation and experimental results. [ABSTRACT FROM AUTHOR]

A hybrid electric unmanned aircraft (HEUA) uses the aerial thermal engine and energy storage system (ESS)-driven electric motor to meet the load demand, thus can be viewed as a “mobile multienergy microgrid.” Conventionally, for a given flight mission, only the energy of an HEUA is optimized while the flight speed is fixed; thus, the overall energy efficiency may be limited. This paper aims to coordinately schedule the energy consumption and the flight speed of an HEUA toward optimal economic and environmental objectives. First, a coordinated optimization model is proposed to coordinately schedule the energy consumption (including the power output of the thermal engine and the ESS) and flight speed (i.e., the true air speed) of an HEUA for simultaneously minimizing the fuel consumption (FC) and polluted gas emission (PGE). Second, a decomposition-based solution method is developed to convert the original nonlinear multiobjective optimization model into a bilevel programming model which can be solved iteratively. Simulation results demonstrate that, compared with the conventional single energy scheduling, the proposed coordinated scheduling method can achieve much better performance in terms of FC and PGE. [ABSTRACT FROM AUTHOR]

This paper describes a high-performance neutral point voltage balancing technique for a neutral point clamped (NPC) converter. Conventional neutral point voltage balancing methods do not function well under low power factor, low pulse ratio, and near-unity modulation index operation conditions. These conditions are essentially dominant operation conditions for aircraft starter/generator systems. This paper introduces an alternative space vector modulation technique for three-level NPC converters in an aircraft starter generator system. The selection of voltage space vectors is optimized for high modulation index and low power factor operation. Disturbances caused by a low pulse ratio are also compensated. The proposed method maintains neutral point voltage balance and ripple minimization over the full range of operating conditions. This paper also provides a detailed analysis of the sources of neutral point voltage imbalances and ripples in high-speed drives with deep flux weakening. Simulation results obtained from a Simulink/PLECS model and experimental results obtained from a 45 kVA, 32 krpm aircraft starter generator test rig prove that the proposed method eliminates the neutral point voltage imbalance and significantly reduces the neutral point voltage ripple. [ABSTRACT FROM AUTHOR]

This paper presents a fast fuzzy logic control algorithm for a Takagi–Sugeno–Kang fuzzy controller, which is applied to integrated \textLED drivers with the purpose of getting a good dynamic response and the reduction in the low-frequency (120 Hz) ripple. The algorithm uses the high-speed mathematical engine of a digital signal controller \text(DSC) that is capable to achieve fast multiplications during a common one-cycle instruction. Therefore, the execution time of the controller is improved with the use of a \textDSC. A scaling procedure is included in the program in order to use and to improve the accuracy of the multiplications and divisions in the \textDSC mathematical engine. A low-range \textDSC was used to program the proposed controller; therefore, the cost is affordable for \textLED driver applications. The fuzzy control curve was approximated to the sliding mode control \text(SMC) curve with the purpose of getting some of the good advantages of the \textSMC strategy like a good dynamic performance. The proposed controller is used to regulate the \textLED current. Simulation and experimental results are shown [ABSTRACT FROM PUBLISHER]

Nonlinear model predictive control (NMPC) requires a repeated online solution of a nonlinear optimal control problem. The computation load remains the main challenge for the real-time practical application of the NMPC technique, particularly for fast systems. This paper presents a fast NMPC algorithm implemented on a field-programmable gate array (FPGA) that employs a particle swarm optimization (PSO) algorithm to handle nonlinear optimization. The FPGA is used to explore the possibilities of parallel architecture for the substantial acceleration of NMPC. PSO is employed to achieve real-time operation due to its naturally parallel capabilities. The proposed FPGA-based NMPC-PSO controller consists of a random-number generator, a fixed-point arithmetic, a PSO solver, and a universal asynchronous receiver/transmitter communication interface. Then, this controller is applied to an engine idle speed control problem and demonstrated with an FPGA-in-the-loop testbench. The experimental results indicate that the NMPC-on-FPGA-chip strategy has good computational performance and achieves satisfactory control performance. [ABSTRACT FROM AUTHOR]

This paper proposes the adaptive extended state observer (AESO)-based active disturbance rejection control (ADRC) to deal with the uncertainties, both in the plant and in the sensors. The gain of ESO is automatically timely tuned to reduce the estimation errors of both states and “total disturbance” against the measurement noise. Furthermore, the satisfactory performance of the closed-loop system is achieved by compensation for uncertainties. This novel controller is applied to the air–fuel ratio (AFR) control of gasoline engine, which has large nonlinear uncertainties due to the unknown speed change, fuel film dynamics, etc. In addition, the measurement of AFR is polluted by sensor noise. The experimental results demonstrate that the proposed controller can ensure high deviation precision of AFR despite both uncertain dynamics and measurement noise. Moreover, the experimental comparison validates the effectiveness of the AESO's gain by which the performance of ADRC on mitigating uncertainties can be improved. [ABSTRACT FROM PUBLISHER]

Judder is the term used in the automotive industry to describe the longitudinal oscillation in a vehicle during its clutch system engagement. Past research has shown that judder can be explained using a behavior of slip speed and temperature captured by the clutch torque. This paper proposes and implements an innovative learning system for better characterization of the judder phenomenon. It is based on a multivariate data-driven analysis from torque signals. Our experimental results have been carried out using the following main resources: dry clutch system, passenger car, test bench, and six different organic facing materials. The multivariate statistical analysis implemented has allowed the development of a computationally efficient and highly accurate learning model to discriminate the torque signals from different facings, using few features and a regularized version of a standard linear classifier. Given this multivariate framework and calculating the correlation pairwisely to a known gold material, it has also been possible to predict judder problem in the vehicle based on a standard test bench in laboratory. We believe that the findings of this paper might reduce significantly the time of development and the cost of testing new friction materials for allowing judder-free performance on vehicles. [ABSTRACT FROM AUTHOR]

Modern engineered systems generally work under complex operational conditions. However, most of the existing artificial intelligence (AI)-based prognostic methods still lack an effective model that can utilize operational conditions data for remaining useful life (RUL) prediction. This paper develops a novel prognostic method based on bidirectional long short-term memory (BLSTM) networks. The method can integrate multiple sensors data with operational conditions data for RUL prediction of engineered systems. The proposed architecture based on BLSTM networks includes three main parts: first, one BLSTM network is used to directly extract features hidden in the multiple raw sensors signals; second, another BLSTM network is employed to learn higher features from operational conditions signals and the learned features from the sensors signals; and, third, fully connected layers and a linear regression layer are stacked to generate the target output of the RUL prediction. Unlike other AI-based prognostic methods, the developed method can simultaneously model both sensors data and operational conditions data in a consolidated framework. The proposed approach is demonstrated through a case study on aircraft turbofan engines, and comparisons with other popular state-of-the-art methods are also presented. [ABSTRACT FROM AUTHOR]

In this paper, a cooperative control of clutch and hydraulic control unit is proposed for the hill-start assist control (HAC) based on the autohold system in order to improve safety and ride comfort. The autohold system model is established as a linear system with bounded uncertainty and disturbance. Then, a novel disturbance-observer-based control is adopted based on an integrated feedforward-feedback compensation, of which the stability and robustness are guaranteed by the $H_\infty$ control theory. The feedforward compensation is recast to a nonlinear and multiobjective optimization problem with some constraints. Finally, the proposed method is verified by the experiments performed on a standard proving ground, and the main results are also provided. [ABSTRACT FROM AUTHOR]

The complex configuration and behavior of multisource hybrid energy systems (HESs) present challenges to their energy management. For a balanced solution, it is especially important to represent and take advantage of the characteristics of each device and the interactive relationship among them. In this paper, multi-agent modeling and a game theory-based control strategy are proposed and combined for the energy management of an example engine–generator/battery/ultracapacitor (UC) HES. The three devices such as engine–generator unit, battery and UC packs are modeled and controlled as independent but related agents, through which the performance and requirements of the individual devices are fully respected. The energy management problem is then formulated as a noncooperative current control (NCC) game. The Nash equilibrium is analytically derived as a balanced solution that compromises the different preferences of the independent devices. The following simulation and experimental results validate the game theory-based control and its real-time implementation. The proposed approach could be further extended to become a general solution for the energy management and control of networked energy systems, in which again fully representing and balancing the different preferences of the components are important. [ABSTRACT FROM PUBLISHER]

This paper investigates a flux-modulated double-rotor machine (FM-DRM) for series–parallel hybrid electric vehicles (HEVs). Based on flux-modulated gears, the FM-DRM has similar speed-torque characteristics. Two configuration schemes are analyzed and compared for the hybrid electric system based on the FM-DRM. The boundary operating conditions of the FM-DRM system are discussed. Moreover, the power flows regarding various operating modes are investigated and corresponding power equations are deduced. An HEV system based on the FM-DRM is simulated for a driving cycle of the United States Environmental Protection Agency to verify the various operating modes. A prototype FM-DRM is manufactured and tested by a driving cycle. The feasibility of using the FM-DRM as a power-splitting device for HEVs is validated by experimental results. [ABSTRACT FROM AUTHOR]

As mobile learning (M-Learning) has demonstrated increasing impacts on online education, more and more mobile applications are designed and developed for the M-Learning. In this paper, a new mobile-optimized application architecture using Ionic framework is proposed to integrate the remote laboratory into mobile environment for the M-Learning. With this mobile-optimized application architecture, remote experiment applications can use a common codebase to deploy native-like applications on many different mobile platforms such as iOS, Android, Windows Mobile, and Blackberry. To demonstrate the effectiveness of the proposed new architecture for M-Learning, an innovative remote networked proportional–integral–derivative control experiment has been successfully implemented based on this new application architecture. The performance is validated by the Baidu mobile cloud testing bed. [ABSTRACT FROM PUBLISHER]

In this paper, a data-driven process controller is designed and implemented onboard a typical marine vessel for optimal variable-speed pump operation, leading to the energy efficiency optimization of its central cooling water system. To match variable flow rate requirements due to changes in the vessel's operational profile with respect to plant limitations, real-time process measurements are used as feedback signals to adjust the parameters and set-points of a data-driven process controller with self-tuned proportional–integral–differential control loops, which is realized through a commercial programmable logic controller and regulates the speed of sea water cooling pumps in order to maximize power saving potential during sea-going and cargo unloading periods. Data-driven control establishes system dynamics according to process parameter variation and ensures system reliability through parameter monitoring, regardless of the controlled plant model. The plant power saving potential is initially examined through a practical case study, whereas experimental results provided after the proposed control system retrofit installation onboard a tanker vessel show significant power balance improvement and reduction of diesel generator fuel consumption compared to existing pump throttle control methods, verifying that marine industry can be greatly benefited from this energy efficiency upgrade. [ABSTRACT FROM PUBLISHER]

A novel wearable vision system is proposed in this article. The wearable system contains a vision glove (EyeGlove) and a wearable display unit, which assists operators with inspection and measurement in confined environments. Three microcameras and an artificial fiducial marker are integrated on the index and middle fingers of the EyeGlove with disjointed camera configurations. Operators can achieve complex camera configurations and movements by using their dexterous hands while wearing the EyeGlove. The wearable vision system distinguishes itself by having two different functions, of which the inspection function uses one or two cameras to inspect in confined environments. For the measurement function, all three cameras and the artificial marker are used to identify object dimensions. Two of the three cameras form a stereovision system with disjointed camera configurations and variable baselines. The third camera and the artificial marker are used to determine the variable baseline in real-time. Inspection and measurement results are presented by the wearable display unit onto a virtual display. To make the wearable vision system adapt to dark environments, three auxiliary LED lights are integrated adjoining the three cameras. Experiments are conducted in both bright and dark environments to verify the measurement accuracy with an average relative error ≤ 5.0%. Furthermore, experiments are also conducted in the confined turbine engine combustor to verify its potential application in industrial environments. [ABSTRACT FROM AUTHOR]

Robust motion control for tracking time-varying reference signals and its application to an electrohydraulic camless engine valve actuator is presented. Two challenging issues encountered in many engineering applications, especially reciprocating machines, are addressed: 1) nonlinear system dynamics and 2) time-varying reference signals. Motion control of the electrohydraulic camless engine valve actuator is a typical example. The electrohydraulic actuator has the critical nonlinear dynamic features such as oil flow through the spool valve orifice and friction force exerting on the piston. The reference valve motion is time-varying since its frequency contents change with the engine speed. Prior to studying the time-varying motion control of a nonlinear system, the time-invariant case is investigated by means of internal model principle. Based on the frequency-domain analysis of a nonlinear feedback system, the high-order time-invariant internal model is designed for tracking performance. Motivated by the time-invariant case, the high-order time-varying internal model is designed for robust tracking of time-varying reference signals. The effectiveness of the proposed time-varying internal model is demonstrated by application to the electrohydraulic camless engine valve actuator. [ABSTRACT FROM PUBLISHER]

In this article, we propose a switching anti-windup scheme for the aircraft engine control. The linear engine model with asymmetric saturation is first transformed into a switched system, each subsystem of which is subject to symmetric saturation. A state-dependent switching logic is presented to orchestrate the switching among multiple anti-windup compensators. We then establish the sufficient condition to guarantee the regional stability and $\mathcal {L}_{2}$ performance of the resulting closed-loop system. This condition is less conservative since the non-symmetric nature of the saturation nonlinearity can be fully exploited in the control design. Optimization algorithms are further developed for the anti-windup gain design. The theoretical aspect of the proposed method is analyzed rigorously, and the effectiveness is validated through experiments performed on a semi-physical test bed. [ABSTRACT FROM AUTHOR]

For a single-shift parallel hybrid electric bus, hybrid-driving with multiple operation modes is adopted for better fuel economy. However, in the process of hybrid-driving, frequent mode transitions (MTs) would be triggered, which are accompanied by extra fuel consumption and abrasion of the clutch, especially for the MTs between engine-on modes and engine-off modes. Therefore, reducing unnecessary MTs and taking advantage of multiple operation modes to improve fuel economy of single-shift parallel hybrid powertrain should be given high priority. To solve this problem, a corrected stochastic model predictive control (MPC) is proposed in this study. First, the Markov-chain based stochastic driver model is built for the statistic of city bus driving cycles. Second, the process of motor starting engine is analyzed based on real-world data and the cost of the process is quantified for optimization. Finally, a novel system operating control strategy based on multiobjective stochastic MPC is proposed. To obtain a better knowledge of the proposed multiobjective control strategy, three kind of commonly used control strategies are adopted for comparison. The simulation results in real-world driving cycles and standard driving cycles show that the proposed energy management strategy can greatly improve the fuel economy of a plug-in hybrid electric bus compared with the equivalent consumption minimization strategy. This study may offer some useful insights for the current strategies to get higher fuel economy. [ABSTRACT FROM PUBLISHER]

A new cryptographic suite (CS) for mutual authentication is proposed on the basis of the next Electronic Product Code Class-1 Generation-2 (C1G2) standard. The Advanced Encryption Standard cryptographic algorithm with a block size of 128-b is used, and a modified output-feedback mode is applied for generating a key, encrypting data, and decrypting data. As a result, the proposed mutual authentication has fast processing speed. To install this CS into the CMOS passive tag, several low-power design techniques are utilized for the digital processor. The fully integrated CMOS security-enhanced passive (SEP) tag is designed and implemented with the Tower 0.18- \mu\m CMOS process. Regardless of secure level on radio-frequency-identification communications, the CMOS SEP tag intercommunicates with the SEP interrogator emulator under a long identification range. In the measured results, the CMOS SEP tag has sensitivities of -12.0 and - 11.6-dBm in insecure and secure communications, respectively. Moreover, it takes a short time of around 40 ms to mutually authenticate a couple of tag and interrogator. Therefore, it is expected to take roughly 1 s for mutual authentications between 25 tags and 1 interrogator. [ABSTRACT FROM PUBLISHER]

A doubly salient electromagnetic starter/ generator (DSESG) system based on the bidirectional converter (BDC) is proposed, in this article. The BDC is operated as an inverter in starting mode and as an active rectifier (AR) in generation mode. Compared to the conventional DSESG system, which is based on an inverter and a diode rectifier or a discrete inverter/rectifier unit (IRU), the configuration is simplified and the weight is reduced. Since the output voltage is improved by the angular position control (APC), field and phase currents are redistributed. The copper loss optimization control (CLOC) for the AR is proposed. The copper loss is analyzed based on the extreme learning machine (ELM) and the turn-off angles are selected. The copper loss is minimized and the heat is reduced. The copper loss and heat generation are also balanced in the field and phase windings to decrease the temperature of the field windings at low speed. Experimental verifications are conducted on a 9 kW DSESG prototype. The effectiveness of the proposed ELM-based CLOC is verified by simulation and experiments. A lighter and simpler DSESG system with reduced loss is presented. [ABSTRACT FROM AUTHOR]

This article proposes a stochastic predictive energy management strategy based on fast rolling optimization for plug-in hybrid electric vehicles (PHEVs). First, combined with a large number of real-world driving cycle data, the stochastic driving behaviors are modeled as probability transition matrices of vehicle demand torque based on Markov chains. Secondly, to solve the torque split problem in parallel hybrid powertrain, the stochastic model predictive control (SMPC) framework is built. Thirdly, the continuation/generalized minimum residual algorithm is employed to execute the fast rolling optimization. The effectiveness of the proposed strategy is validated in both simulations and test bench, and its performance is compared with the SMPC by dynamic programming (DP) optimization and the equivalent minimum fuel consumption strategy (ECMS). Simulation results show that under real-world driving cycle, PHEV using the proposed strategy could obtain 4.8% energy consumption reduction comparing with that uses ECMS. In terms of computational time, the proposed strategy dramatically reduces the running time comparing with that of SMPC by DP optimization. Furthermore, the similar results can be obtained in the experiment. Under real-world driving cycle, 4.6% fuel economy improvement is obtained using the proposed strategy compared with that using ECMS, which clearly shows that the proposed strategy is effective. [ABSTRACT FROM AUTHOR]

Series hybrid electric vehicles improvements in fuel consumption and emissions directly depend on the operating point of the auxiliary power unit (APU). In order to balance the conflicting goals of fuel consumption and emissions reduction in the choice of operating point, the APU operating point optimization problem is formulated as a constrained multi-objective optimization problem with competing objectives of fuel-electricity conversion cost, HC emissions, CO emissions, and NOx emissions first. Then, the adaptive multi-objective differential evolution (AMODE) algorithm is proposed to solve the APU operating point multi-objective optimization problem. It adopts an external elitist archive to store the nondominated solutions that are found during the evolutionary process. The innovative adaptive mutation operator of the AMODE ensures its high searching ability, and the adaptive grids mechanism improves the diversity of the resulted Pareto solutions effectively. Finally, bench experiments under four typical driving cycles are performed and comparisons are made between the results of the proposed multi-objective optimization approach (MOA), the exponential weighted approach, and the traditional single objective approach. The experimental results show that the proposed AMODE-based MOA improves the APU emissions significantly, at the expense of a slight drop in fuel efficiency. [ABSTRACT FROM PUBLISHER]

A system compensator is designed to cancel the mechanical characteristics of a power electronics-controlled induction motor drive with a coupled electrical generator system. The emulation scheme using the compensator enables accurate emulation of high-speed and high-power mechanical system dynamics. The compensator is developed based on the system transient response of the test rig, considering the full operating range of the test system. The design process of the compensator is described, and it is validated in both the time and frequency domains. Finally, the effectiveness of the compensator is demonstrated by simulation and experimental emulation of aero gas engine dynamics. [ABSTRACT FROM PUBLISHER]