KEYWORDS: Safety, Control systems, Data modeling, Statistical analysis, Detection and tracking algorithms, Data centers, Adaptive control, Expectation maximization algorithms, Algorithm development
A novel ACC algorithm that fully considers the characteristics of the driver is proposed in order to improve satisfaction
and acceptance of the commercial Adaptive Cruise Control (ACC) system in this paper. Firstly, the driving style is analyzed
based on the driving data collection through the GMM-KL algorithm, and then the driver model is established and the
driver’s sensitivity to tracking error is analyzed and discussed; Afterwards, an MPC-based ACC algorithm is designed
which comprehensively considers multiple objectives including the ride comfort, the driving safety and the traffic
efficiency. The weighting adjustment mechanism according to the sensitivity analysis is introduced to truly reflect driving
fondness of drivers with different driving styles. The simulations show that the proposed ACC algorithm in this paper can
achieve reasonable expectation during the car-following and demonstrate the driving habits for drivers, which will help to
enhance the adaptability of the ACC system.
Asymmetric rotor bearing (ARB) is a special rotor bearing system, misalignment and clearance of spline in ARB system bring in multiple nonlinear forces and moments, which may cause premature failures to the rotary machines. In this study, a nonlinear dynamic model considering the parallel misalignment, angular misalignment and manufacturing level of the spline was established, and the vibration characteristics of these factors on the ARB system were analyzed to explore the vibration characteristics of ARB system under multi-source nonlinear excitation. The results show that the manufacturing level of the spline has a great influence on the lateral vibration. Parallel misalignment changes vibration response by changing the backlash distribution. Angular misalignment excites high-frequency vibration of the ARB system. Provide a theoretical basis for the design, vibration suppression and fault diagnosis of ARB systems.
A novel flow-mode magneto-rheological (MR) engine mount integrated a diaphragm de-coupler and the spoiler plate is designed and developed to isolate engine and the transmission from the chassis in a wide frequency range and overcome the stiffness in high frequency. A lumped parameter model of the MR engine mount in single degree of freedom system is further developed based on bond graph method to predict the performance of the MR engine mount accurately. The optimization mathematical model is established to minimize the total of force transmissibility over several frequency ranges addressed. In this mathematical model, the lumped parameters are considered as design variables. The maximum of force transmissibility and the corresponding frequency in low frequency range as well as individual lumped parameter are limited as constraints. The multiple interval sensitivity analysis method is developed to select the optimized variables and improve the efficiency of optimization process. An improved non-dominated sorting genetic algorithm (NSGA-II) is used to solve the multi-objective optimization problem. The synthesized distance between the individual in Pareto set and the individual in possible set in engineering is defined and calculated. A set of real design parameters is thus obtained by the internal relationship between the optimal lumped parameters and practical design parameters for the MR engine mount. The program flowchart for the improved non-dominated sorting genetic algorithm (NSGA-II) is given. The obtained results demonstrate the effectiveness of the proposed optimization approach in minimizing the total of force transmissibility over several frequency ranges addressed.
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