Search

Human driving behavior significantly affects vehicle fuel economy and emissions on hilly roads. This paper presents an ecological (eco) driving scheme (EDS) on hilly roads using nonlinear model predictive control (NMPC) in a mixed traffic environment. A nonlinear optimization problem with a relevant prediction horizon and a cost function is formulated using variables impacting the fuel economy of vehicles. The EDS minimizes vehicle fuel usage and emissions by generating the optimum velocity trajectory considering the longitudinal motion dynamics, the preceding vehicle's state, and slope information from the digital road map. Furthermore, the immediate vehicle velocity and angle of the road slope are used to tune the cost function's weight utilizing fuzzy inference methods for smooth maneuvering on slopes. Microscopic traffic simulations are used to show the effectiveness of the proposed EDS for different penetration rates on a real hilly road in Fukuoka City, Japan, in a mixed traffic environment with the conventional (human-based) driving scheme (CDS). The results show that the fuel consumption and emissions of vehicles are significantly reduced by the proposed NMPC-based EDS compared to the CDS for varying penetration rates. Additionally, the proposed EDS significantly increases the average speed of vehicles on the hilly road. The proposed scheme can be deployed as an advanced driver assistance system (ADAS). [ABSTRACT FROM AUTHOR]

Model predictive control has been wildly used in the modern power electronic converter with the advantages of the multi‐objective optimization, no additional modulator is required and small grid current harmonic. However, the switching operation is not constant and higher sampling frequency must be required. A novel direct power control using model predictive control (DPC‐MPC) strategy is presented in this paper, which achieve the optimal vector prediction scheme with constant switching frequency operation. The calculation process is greatly simplified due to the optimal voltage vector generated directly, then, it applied to the control of a three‐phase three‐level T‐type grid converter. A cost function is first built to balance the neutral‐point‐potential voltage. After then, the cost function is updated by considering the delay caused by the calculation, sampling and gate driver. Finally, a comprehensive comparative study with the conventional DPC‐MPC strategy is introduced to verify the superiority of the presented DPC‐MPC. The simulation and experimental results show that the steady and the transient performance of the grid current with the proposed DPC‐MPC control strategy are effectively improved. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Virtual vector is applied in neutral‐point‐clamped (NPC) three‐level converter finite control set model predictive control (FCS‐MPC) strategy due to its good performance of less current ripples and high power efficiency. However, in the process of adding virtual vectors, some redundant virtual vectors will be selected. Excessive virtual vector will increase the computational burden and affect grid‐tied current performance. A virtual vector optimal selection strategy for model predictive control to determine the vectors is proposed. The strategy calculates the fluctuation of grid‐tied current through theoretical analysis. Based on the analysis of amplitude fluctuation of grid‐tied current, the graphics of coverage angle visualization can be obtained under different virtual vector. The angle of the required virtual vectors is obtained through the graphics of coverage angle visualization. The number of virtual vector can be determined when the error current angle range covers the entire vector graph. The proposed control strategy was compared with the conventional control strategies, including excessive virtual vectors or with no any virtual vector. Experimental results show that the proposed control strategy can significantly reduce THD, grid‐tied current error and computational burden. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Current control of the grid‐connecting inverters usually has an important influence on the control performance especially when the inverters operate at a low‐switching frequency for it would result in a severe harmonic distortion in the output current components. To improve the current control performance, a novel model predictive current control (MPCC) strategy based on an effective harmonic extraction method was present for a high‐power three‐level NPC inverter in this paper. First, an effective amplitudes extraction method called generalized sliding discrete Fourier transform (GSDFT) was designed for the fundamental and low‐order harmonic current components, and which would be taken as a part of the cost function for the MPCC besides the consideration of switch losses and neutral point potential balancing issues. Experimental results verify that this kind of novel control strategy not only has a characteristic similar with the selective harmonic elimination, also could realize a nice current control performance even the switching frequency is low than 500 Hz as well as a neutral point potential balancing. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, to solve the problem of large torque ripple in a switched reluctance motor (SRM), a new control strategy based on model predictive flux control is proposed in the direct torque control (DTC) algorithm. First, the flux linkage value in the next period is calculated from the discrete time model of the SRM. Second, to reduce the computation burden and increase the dynamic response, a torque hysteresis controller is embedded in the system to select three candidate voltage vectors for the cost function. Finally, based on flux linkage minimization, the best voltage vector is selected and applied to the system. The proposed direct torque and predictive flux control (DTPFC) method perfectly suits the nonlinear magnetic characteristics of SRM, and shows better steady‐state and dynamic‐state performances compared to DTC. Furthermore, since DTPFC has only one variable in the cost function, the huge task of obtaining the best weighting factor is eliminated. Simulation and experiments are carried out on a three‐phase 12/8 SRM with the proposed control algorithm and DTC. The results demonstrate the validity of the new control approach. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]