TMPT: multi-body package SIMPACK

Eichberger, Alex; Hofmann, Gerhard

doi:10.1080/00423110701803385

Cited by 6 publications

(3 citation statements)

References 4 publications

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“…The relationship between the wheel and the road uses the Pacejka Similarity type [20], which has taken into account the stiffness and damping ratio of 200 kN/m and 75 Ns/m, along with other parameters. Research by Eichberger and Hofmann [21] shows the wheel relationship and becomes the main factor in conducting vehicle modeling in multibody dynamic simulations.…”

Section: Multi-body Dynamic Simulationmentioning

confidence: 99%

Electric Delta Trike Stability Characteristic and Maneuverability Analysis: Experiment and Multi-Body Dynamic Simulation

Nurprasetio

Widyantara

Budiman

et al. 2022

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This paper reveals the stability characteristics of an electric-powered delta trike (e-trike), which is developed for goods delivery services. The changeable center of gravity position and weight due to electric component placement and the carried good weight can cause instability of the e-trike. Three main parameters are firstly evaluated on the e-trike: 1) geometry, 2) center of gravity, and 3) stiffness and damping coefficient of the suspensions. Single Lane-Change (SLC) and Double Lane-Change (DLC) tests were then conducted following ISO 14791:2000 and ISO 3888-1:2018 standards, respectively. An e-trike model was created and simulated using SIMPACK, a multi-body dynamic software. The simulation results showed that the developed e-trike model can replicate SLC and DLC tests, indicating the model was valid. A parametric study with the validated model was then conducted with various e-trike weights, center of gravity position, and suspension stiffness and damping ratio values. The results showed additional weight and higher center of gravity position can decrease threshold velocity to avoid rollover. The low suspension stiffness also contributed to lower the threshold velocity. However, the damping coefficient value did not change the threshold velocity significantly. These results can be a guideline in designing a delta trike with better performance in stability and maneuverability.

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Section: Multi-body Dynamic Simulationmentioning

confidence: 99%

Electric Delta Trike Stability Characteristic and Maneuverability Analysis: Experiment and Multi-Body Dynamic Simulation

Nurprasetio

Widyantara

Budiman

et al. 2022

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“…Generally, a bogie suspension system is composed of the elastic element and the damper element; it mainly includes two important parameters to be designed, i.e., the spring static deflection value and the suspension damping parameter value. In order to obtain an accurate and reliable design result for the suspension damping parameter, one widely used method is to use computer simulation technology and vehicle dynamic analysis software to optimize and determine the final value [2] to [4]. This method can simulate the actual operation of railway vehicles well [5] and [6] and can achieve a more accurate design result.…”

Section: Introductionmentioning

confidence: 99%

Analytical Formulae and Applications of Vertical Dynamic Responses for Railway Vehicles

Yu¹,

Song²,

Zhao³

et al. 2023

sv-jme

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To effectively improve the estimated level of railway vehicles’ vertical dynamic responses and provide a more suitable reference for the selection of its secondary suspension damping parameter, this paper has derived the root mean square values analytical formulae of the car body vertical acceleration, the secondary suspension vertical stroke, and the axle box vertical action force for railway vehicles under the random excitation of the track closer to the actual track characteristics. The correctness of the analytical formulae is verified by testing a real vehicle. Then, according to the analytical formulae derived, an analytical design method of the optimal damping ratio for the secondary suspension system is constructed based on the multi-objective programming and single-objective interval constraint analysis, which can be used to find the best trade-off for conflicting performance indices, such as ride comfort, running smoothness, and running safety, and the influences of the system parameters on the optimal damping ratio are analysed. This research can effectively characterize the vertical vibration response of railway vehicles and provide an effective reference for the initial design of the railway vehicle secondary suspension damping parameter.

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“…Therefore, the nature of train dynamics during high speeds should be carefully studied before any new design [5] or prototype development is conducted. Computer modeling and simulation is widely used in those studies, and powerful computer packages [6][7][8][9] are also available commercially for pertinent applications, such as the multi-body system dynamics package ADAMS [7] or SIMAPCK [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Multi-Body System Dynamics Modeling of a Locomotive for its In-Service Parameter Effects Prediction

Fan

Wang

2013

AMM

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To understand the nature of train dynamics to its in-service parameter effects during high operational speeds, multi-body system (MBS) modeling of a Chinese locomotive SS9 was performed. Following comparison of the field test data with the simulation result shows that they agree with each other with considerable accuracy, thus, the MBS model established is validated and being effective for further dynamics studies. For demonstration, a case study was conducted and demonstrates that with the increase of effective series stiffness, the hydraulic yaw damper could dissipate the lateral vibration energy of the front bogie significantly.

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TMPT: multi-body package SIMPACK

Cited by 6 publications

References 4 publications

Electric Delta Trike Stability Characteristic and Maneuverability Analysis: Experiment and Multi-Body Dynamic Simulation

Electric Delta Trike Stability Characteristic and Maneuverability Analysis: Experiment and Multi-Body Dynamic Simulation

Analytical Formulae and Applications of Vertical Dynamic Responses for Railway Vehicles

Multi-Body System Dynamics Modeling of a Locomotive for its In-Service Parameter Effects Prediction

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