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This paper presents the road simulator control technology for reproducing a road input signal to implement real road data. The simulator consists of a hydraulic pump, a servo valve, a hydraulic actuator and its control equipment. QFT (Quantitative Control Theory) is utilized to control the simulator effectively. The control system illustrates a tracking performance of the closed-loop controller with a low order transfer function G(s) and a pre-filter F(s) for a parametric uncertainty model. A force controller is designed to communicate the control signal between the simulator and digital controller. Tracking specification is satisfied with upper and lower bound tolerances on the steep response of the system to the reference signal. The efficacy of the QFT force controller is verified through the numerical simulation in which combined dynamics and actuation of the hydraulic servo system are tested. The simulation results show that the proposed control technique works well under an uncertain hydraulic plant system. The conventional software (Labview) is used to make up for the real controller on a real-time basis, and the experimental works show that the proposed algorithm works well for a single road simulator.

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This paper presents the design of a quantitative feedback control system for a three-axis hydraulic road simulator. The road simulator is a multiple input-output (MIMO) system with parameter uncertainties which should be compensated with a robust control method. The objective of the present paper is to reproduce the random input signal or real road vibration signal by three hydraulic cylinders. The replaced m 2 MISO equivalent control system is suggested, which satisfies the design specification of the original mxm MIMO control system by decoupling each of the three axes. Quantitative Feedback Theory (QFT) is used to control the simulator. The QFT illustrates a tracking performance of the closed-loop controller with low order transfer function G (s) and pre-filter F (s) having the minimum bandwidth for the uncertain plant with parameter uncertainty. The efficacy of the designed controller is verified through dynamic simulation, which is co-simulated with hydraulic models of Matlab and Adams multi-body. The simulation and the experimental results show that the proposed control technique works well for uncertain hydraulic plant systems.

Summary In this article, a nondissipative equalization scheme is proposed to reduce the inconsistency of series connected lithium‐ion batteries. An improved Buck‐Boost equalization circuit is designed, in which the series connected batteries can form a circular energy loop, equalization speed is improved, and modularization is facilitated. This article use voltage and state of charge (SOC) together as equalization variables according to the characteristics of open‐circuit voltage (OCV)‐SOC curve of lithium‐ion battery. The second‐order RC equivalent circuit model and back propagation neural network are used to estimate the SOC of lithium‐ion battery. Fuzzy logic control (FLC) is used to adjust the equalization current dynamically to reduce equalization time and improve efficiency. Simulation results show that the traditional Buck‐Boost equalization circuit and the improved Buck‐Boost equalization circuit are compared, and the equalization time of the latter is reduced by 34%. Compared with mean‐difference algorithm, the equalization time of FLC is decreased by 49% and the energy efficiency is improved by 4.88% under static, charging and discharging conditions. In addition, the proposed equalization scheme reduces the maximum SOC deviation to 0.39%, effectively reducing the inconsistency of batteries.