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Wheel force transducers (WFTs) have performance characteristics that make them attractive for applications in endurance evaluation of road vehicles, ride and handling optimization, tire development and vehicle dynamics. As a WFT is mounted on the the driven wheel, the loads on the wheel and the outputs of WFTs are usually nonlinearly related. Thus, a real-time filter is needed to measure the true loads on the wheel.

In this paper, a new nonlinear filtering algorithm utilizing quadrature Kalman filter (QKF) is proposed to track the actual loads in real time through establishing the specific observation equations with Singer models.

The simulation results show that the accuracy and the rapidity of QKF outperforms the capability of the unscented Kalman filter (UKF). Then, the dynamic tests on the MTS testing platform give the comparisons between the real-time QKF and the wavelet transform, where the former has superior dynamic accuracy. Finally, the practical tests of shifting and braking on a real vehicle confirm the effectiveness of QKF, which further validates the proposed method fitting reality.

In this paper, a newly improved algorithm with QKF for WFT has been proposed and tested experimentally. As the wheel loads are always time-varying and complex, introducing Gaussian noise in the outputs of the transducer, WFT-suitable Singer model and WFT measurement equation base on a QKF are established. The experiment results show that QKF has advanced performance than the traditional UKF. Also, the road wheel test bed produced by MTS has been exploited as the test platform to demonstrate the dynamic efficiency of the proposed real-time filter under various operating conditions for a wide range of loads. And, the practical tests with the real vehicle are accomplished to verify the value and effectiveness of the proposed method.

This paper aims to gain the real-time terrain parameters of the battlefield for the evaluation of military vehicle trafficability. In military missions, improvements in vehicle mobility have the potential to greatly increase the military operational capacity, in which vehicle trafficability plays a significant role.

In this framework, an online terrain parameter estimation method based on the Gauss-Newton algorithm is proposed to estimate the primary terrain mechanical parameters. Good estimation results are indicated, unless the initial values involved are properly selected. Correspondingly, a method of terrain classification is then presented to contribute to the selection of the initial values. This method uses the wavelet packet transform technique for feature extraction and adopts the support vector machine algorithm for terrain classification. Once the terrain type is identified, advices can be given on the initial value selection referring to the empirical terrain parameters.

On the basis of a dynamic testing system suitable for real military vehicles, the proposed algorithms are validated. High estimation accuracy of the terrain parameters is indicated on sandy loam, and good classification performance is demonstrated on four tested terrains.

The presented algorithm outperforms the existing methods, which not only realizes the online terrain parameter estimation but also develops the estimation accuracy. Moreover, its effectiveness is confirmed by real vehicle tests in practice.

The purpose of this paper is to present a prototype simulation system for driving performance of an electromagnetic unmanned robot applied to automotive test (URAT) to solve that it is difficult and dangerous to online debug control program and to quickly obtain test vehicle dynamic performance.

The driving performance of the electromagnetic URAT can be evaluated by the prototype simulation system. The system can simulate various driving conditions of test vehicles. An improved vehicle longitudinal dynamics model matching to the electromagnetic URAT is established. The proposed model has good real-time, and it is easy to implement. The displacement of throttle mechanical leg, brake mechanical leg, clutch mechanical leg and shift mechanical arm is used for the system input. Test vehicle speed and engine speed are used for the system output, and they are obtained by the computation of the established vehicle longitudinal dynamics model.

Driving conditions simulation test and vehicle emission test are performed using a Ford Focus car. Simulation and experiment results show that the proposed prototype simulation system in the paper can simulate the driving conditions of actual vehicles, and the performance that electromagnetic URAT drives an actual vehicle is evaluated by the simulation system.

Future research will focus on improving the real time of the proposed simulation system.

The autonomous driving performance of electromagnetic URAT can be evaluated by the proposed prototype simulation system.

A prototype simulation system for driving performance of an electromagnetic URAT based on an improved vehicle longitudinal dynamics model is proposed in this paper, so that it can solve the difficulty and danger of online debugging control program, quickly obtaining the test vehicle performance.

The core of the successful implementation of the integrated project delivery (IPD) mode is to establish a high-quality relationship of cooperation, trust and sharing among participants. This paper proposes recommendations to improve the relationship quality of participants from the owner's perspective. The results provide the theoretical basis and practical guidance for the popularization and application of the IPD mode.

This paper analyzes the dynamic relationship among participants in IPD mode based on supply chain theory and similarity theory. A tripartite game model of the owner, designer and the contractor is constructed to obtain the evolutionary equilibrium strategies under different parameter constraints. Then, numerical simulations under various scenarios are conducted to explore the dynamic evolution and the influencing factors of the relationship quality among the participant in the IPD mode.

The results show that (1) the relationship quality under certain conditions gradually improves as the project progresses until stable and high-quality cooperation is formed and (2) the owner's positive supervision cost, the distribution coefficient of incentive and punishment of participants and the scale of incentive pool are important factors influencing the relationship quality.

This study incorporates the following three innovations. First, analyzing the relationship quality among the participants of IPD mode based on supply chain theory. Second, the evolutionary game theory is applied to the relationship quality analysis. Third, conclusion innovation. The authors conclude that the relationship quality may progress, decrease or cycle with the progress of the project and targeted recommendations are presented based on the results.