Yuanchang Chen

This paper presents a novel vehicle dynamic controller for coordinating the Electronic Stability Program (ESP) and active suspension system (ASS) to improve the directional performance and roll stability of the vehicle. The controller consists of two levels. The upper level is responsible for monitoring system status, determining control objectives, and distributing the active forces. Also, a priority-weighting mechanism is proposed for model predictive control to generate an adaptive multi-objective cost function. Then, the distribution of active forces is obtained by solving a centralized optimization problem. In the lower level, the dynamics of the suspension actuators are taken into consideration in the control of suspension forces for the ASS, and the desired braking forces are achieved through braking torque control for the ESP. The effectiveness of the proposed controller is verified through numerical simulation by using a nonlinear full vehicle model. The simulation results show that the proposed dynamic controller can significantly improve the yaw and roll performance of the vehicle.

A Damage Indication Function (DIF) is developed in this work to localise the damage on a structure. The novelty is that this is the first work proposing a time response correlation-based damage localisation method. To identify the damage, dynamic time response is measured by several sensors placed on the structure using a user excitation. A set of damaged finite element models is developed. Each damage model has only one specified damage but at different locations. The collection of the damage models forms a complete damage grid. The same user excitation is applied to each damage model to generate an analytical response. The test response is then correlated with the model response of each damage model. The highest correlation between the test response and the model response of all damage models would indicate the damage location on the test structure. A plate-type structure is used to demonstrate the power and effectiveness of DIF experimentally.

Wind turbine design and operation will benefit from a better understanding of blade dynamics. Usually, only one surface or one side of a 3D structure is measured in Scanning Laser Doppler Vibrometer (SLDV) tests due to test setup and instrumentation limitations. However, in this work, we demonstrate an approach to overcome these limitations while also using an SLDV that provides high spatial resolution measurement. In the case of a wind turbine blade, only one surface is typically measured; however, it is beneficial to investigate both blade global modes and the relative motions of the two blade surfaces by using both numerical models and experimental tests. This work creatively develops both experimental and numerical approaches to investigate the dynamics and the relative motions of both surfaces of the wind turbine blade from global and local perspectives. On the experimental side, experimental modal testing is conducted on both surfaces of the wind turbine blade with a high spatial resolution 3D SLDV. The two surfaces of the wind turbine blade are measured and stitched together to build the blade experimental mode shapes of both surfaces. A total of over 1500 points are scanned from both surfaces of the blade in a non-contact fashion to obtain not only the global bending modes (flap-wise and edge-wise), the global torsional modes, but also the localized panel mode shapes. On the numerical side, a finite element model of the blade is developed to obtain the numerical mode shapes. The experimental mode shapes on either one surface or both surfaces of the blade are used to validate the blade finite element model. The mode shape correspondence between the model and the test is also identified. With the availability of both experimental and numerical mode shapes, localized panel modes of the wind turbine blade are observed and characterized, and as a result the numerical model is validated. This work provides useful case studies for the design and structural analysis of wind turbine blades based on both the experimental observations and the validation of numerical models typical of those used for blade design and blade structural analysis.

To address the contradiction between ride comfort and handling stability, a new vibration-absorbing wheel structure with time-delay feedback control was proposed by applying a time-delay feedback-controlled dynamic vibration absorber to the wheel structure. Using H₂ optimization and the particle swarm optimization algorithm (PSO), the design parameters of the time-delay vibration-absorbing wheel structure were obtained with sprung mass acceleration (SMA), suspension deflection (SD) and dynamic tire deflection (DTD) as the optimization objective functions. The stability interval of the system was analyzed using the Routh–Hurwitz criterion and the Sturm criterion. The vehicle vibration reduction performance of the new vibration-absorbing wheel structure was simulated and verified in the time domain under harmonic excitation and random excitation. The simulation results show this new structure can effectively solve the contradiction between the ride comfort and handling stability. It provides a new technical idea for reducing vehicle vibration.

The mode shapes of beam-type structures, such as aircraft wings and wind turbine blades, involve a high degree of coupling between bending and torsional deformations. In the case of wind turbine blades, different types of deformation are typically easily recognized by visual observation. However, this visual approach is sometimes challenging for high-order mode shapes, which involve complex coupling of both bending and torsional deformations. This work proposes a novel mode shape recognition algorithm, called the finite cross-section method (FCSM), for application to highly coupled beam-type structures not only to identify the deformation components of complex beam mode shapes but also more importantly to quantify their respective relative contribution. In the application case study for the FCSM, the entire structure is discretized into multiple cross sections. The flap-wise, edge-wise, and torsional deformation components of the entire structure are determined at the cross-section level. The deformation components of the entire structure and their respective contribution are obtained from assembling all cross sections. To validate the mode shape recognition performance, FCSM is applied to and demonstrated on four test cases: (1) numerical mode shapes of a simple cantilever beam, (2) numerical mode shapes from a straight wind turbine blade, (3) numerical mode shapes of a swept wind turbine blade, and (4) experimental mode shapes from a high spatial resolution 3D scanning laser Doppler vibrometer (SLDV) modal test. Both numerical and experimental studies demonstrate that FCSM can successfully recognize the quantitative contribution of flap-wise, edge-wise, and torsional deformation.

To reduce seat vibration caused by uneven road surfaces, the time-delay feedback control into the seat suspension system was introduced and an active seat suspension control method based on time-delay feedback was proposed in this paper. A three-degree-of-freedom (3-DOF) suspension model with time-delay feedback control was established. The time-delay independent stability region and critical stability curve of the system were derived using the method of characteristic root and stability switching. The effect of feedback control parameters on system vibration was investigated in the stability region. The seat acceleration (SA), body acceleration (BA), suspension dynamic deflection (SDD), and tire dynamic displacement (TDD) were used as multi-objective optimization functions and the optimal values of feedback control parameters were obtained based on the particle swarm algorithm (PSO) with above optimization functions. The numerical simulation was conducted to validate the proposed model. The simulated results show that the time-delay feedback control can significantly suppress the vibration response of the seat and effectively improve the suspension performance under different road excitation compared with the passive suspension. It can be seen that the active seat suspension with time-delay control significantly improve ride comfort and handling stability of the vehicle, which can be used as a reference for the active control technology of vehicle suspension.

Integrated motor-transmission (IMT) powertrain systems are widely used in future electric vehicles due to the advantages of their simple structure configuration and high controllability. In electric vehicles, precise speed tracking control is critical to ensure good gear shifting quality of an IMT powertrain system. However, the speed tracking control design becomes challenging due to the inevitable time delay of signal transmission introduced by the in-vehicle network and unknown road slope variation. Moreover, the system parameter uncertainties and signal measurement noise also increase the difficulty for the control algorithm. To address these issues, in this paper a robust speed tracking control strategy for electric vehicles with an IMT powertrain system is proposed. A disturbance observer and low-pass filter are developed to decrease the side effect from the unknown road slope variation and measurement noise and reduce the estimation error of the external load torque. Then, the network-induced delay speed tracking model is developed and is upgraded considering the damping coefficient uncertainties of the IMT powertrain system, which can be described through the norm-bounded uncertainty reduction method. To handle the network-induced delay and parameter uncertainties, a novel and less-conservative Lyapunov function is proposed to design the robust speed tracking controller by the linear matrix inequality (LMI) algorithm. Meanwhile, the estimation error and measurement noise are considered as the external disturbances in the controller design to promote robustness. Finally, the results demonstrate that the proposed controller has the advantages of strong robustness, excellent speed tracking performance, and ride comfort over the current existing controllers.