Compared with dual-mass flywheel (DMF) and DMF with simple-type centrifugal pendulum vibration absorber (CPVA), DMF with bifilar-type CPVA has a better damping performance in the whole speed range of engine. The related research mainly focused on local models, such as dynamic model of DMF and dynamic model of CPVA, and the effect of the curvature path of CPVA on the damping performance. The reported models and methods are not sufficient for the system of DMF coupled with bifilar CPVA. Aiming at the deficiency of local models and the limitation of bench test, an integral model for DMF with bifilar CPVA is proposed and the real vehicle test is carried out in this study. Involving the moment of inertia of the centrifugal pendulum, the model considers the nonlinearities of DMF and bifilar CPVA. Afterward, the dynamic model of the automobile power transmission system equipped with the DMF with bifilar-type CPVA is built, and the dynamic responses of the system are investigated under idling and driving conditions. According to the simulation results, DMF with bifilar-type CPVA shows better vibration reduction performance in full-speed range. Moreover, the key structural parameters R and l influencing the damping performance of DMF with bifilar CPVA are discussed. The results show that the sum of R and l is directly proportional to the damping effect. Finally, real vehicle tests under idling and driving conditions (engine speed from 750 r/min to 3400 r/min) are carried out. The test results show that the 2nd order engine speed fluctuations are attenuated by more than 80% by DMF with bifilar CPVA with engine speed lower than 2000 r/min and are attenuated by more than 90% with engine speed higher than 2000 r/min. The experimental results are basically consistent with the simulation results, which verify the validity of the model.
Autonomous driving technology is one of the currently popular technologies, while positioning is the basic problem of autonomous navigation of autonomous vehicles. GPS is widely used as a relatively mature solution in the outdoor open road environment. However, GPS signals will be greatly affected in a complex environment with obstruction and electromagnetic interference, even signal loss may occur if serious, which has a great impact on the accuracy, stability and reliability of positioning. For the time being, L4 and most L3 autonomous driving modules still provide registration and positioning based on the high-precision map constructed. Based on this, this paper elaborates on the reconstruction of the experimental scene environment, using the SLAM (simultaneous localization and mapping) method to construct a highprecision point cloud map. On the constructed prior map, the 3D laser point cloud NDT matching method is used for real-time positioning, which is tested and verified on the “JAC Electric Vehicle” platform. The experimental results show that this algorithm has high positioning accuracy and its real-time performance meets the requirements, which can replace GPS signals to complete the positioning of autonomous vehicles when there is no GPS signal or the GPS signal is weak, and provide positioning accuracy meeting the requirements.
Stable, real-time, drivable area planning in a dynamic environment is an essential feature of autonomous vehicles. This paper presents an efficient 3D laser radar-based drivable area planning algorithm. In order to extract the drivable area, the original point cloud data is first downsampled to obtain a relatively sparse point cloud to reduce the complexity. Then, based on the geometric features of the pavement point and dividing the road plane, the obstacle point after the road plane is divided. The cloud is transformed into a 2D aerial view, and a series of expansion, convolution and other regional operations are performed on the bird's-eye view, and the road edge points are extracted, and the curve fitting is performed based on the least squares method to plan the drivable region. The algorithm proposed in this paper was tested on the KITTI dataset and obtained robust, high-efficiency experimental results.
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