On the cosimulation of multibody systems and hydraulic dynamics

Rahikainen, Jarkko; González, Francisco Javier Miranda; Naya, Miguel Ángel; Sopanen, Jussi; Mikkola, Aki

doi:10.1007/s11044-020-09727-z

Cited by 31 publications

(20 citation statements)

References 34 publications

(52 reference statements)

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“…17. A similar system was initially described in [21], and modified versions were later included as benchmarks in [25] and [28]. The example here is the same as used in [25], although a different manoeuvre is performed in the numerical tests.…”

Section: Hydraulic Cranementioning

confidence: 99%

Energy-based monitoring and correction to enhance the accuracy and stability of explicit co-simulation

Rodríguez

Sputh

et al. 2022

Multibody Syst Dyn

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The simulation of complex engineering applications often requires the consideration of component-level dynamics whose nature and time-scale differ across the elements of which the system is composed. Co-simulation offers an effective approach to deal with the modelling and numerical integration of such assemblies by assigning adequate description and solution methods to each component. Explicit co-simulation, in particular, is frequently used when efficient code execution is a requirement, for instance in real-time setups. Using explicit schemes, however, can lead to the introduction of energy artifacts at the discrete-time interface between subsystems. The resulting energy errors deteriorate the accuracy of the co-simulation results and may in some cases develop into the instability of the numerical integration process. This paper discusses the factors that influence the severity of the energy errors generated at the interface in explicit co-simulation applications, and presents a monitoring and correction methodology to detect and remove them. The method uses only the information carried by the variables exchanged between the subsystems and the co-simulation manager. The performance of this energy-correction technique was evaluated in multi-rate co-simulation of mechanical and multiphysics benchmark examples.

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Section: Hydraulic Cranementioning

confidence: 99%

Energy-based monitoring and correction to enhance the accuracy and stability of explicit co-simulation

Rodríguez

Sputh

et al. 2022

Multibody Syst Dyn

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“…The computational numerical model is subjected to load conditions that are set in the simulation model by commands for the movement of joints. Their timing is established along a unified time axis for the movement commands corresponding to the methodology sequence given in this paper [15][16][17]. Equations of motion have been found for each element of the system.…”

Section: Introductionmentioning

confidence: 99%

“…The control forces in the hydraulic circuit of this mechanism must be designed in the prototype of the machine so that they would sufficiently enable load handling as well as operation with the harvester head. These force assumptions in the hydraulic circuit can be found using a simulation in the Multibody System with a sufficiently accurate model of the machine, boundary and operating conditions [15,17]. Currently, the MSC Adams software only offers the solution of mechanical operations and mechanisms [21].…”

Section: Introductionmentioning

confidence: 99%

Verifying the Lifting and Slewing Dynamics of a Harvester Crane with Possible Levelling When Operating on Sloping Grounds

Mergl

Kašpárek

2022

Forests

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This paper focuses on the force and torque load of a harvester hydraulic crane employed on sloping grounds, both levelled and not levelled. Field research was conducted for this purpose and the results were compared with a dynamic analysis of the crane in MSC Adams. It was found that levelling the slewing platform of the crane is necessary for use on sloping grounds, primarily because the effect on the force and lifting torques is reduced. The research showed that when the slope of the slewing gear is up to −12°, the lifting torque reaches a higher maximum lifting force than when the slewing gear is in a horizontal position (0°). As part of the theoretical verification by a dynamic analysis of the crane and the AH6 machine, a different pressure was detected in the lifting cylinder of the crane compared to the field research. The total deviation between the simulation and the field research was 9.82%. The slewing torque of the hydraulic crane without the slewing bearing being levelled can be characterized 97.38% by a parabola whose vertex is located in front of the front part of the machine and falls as the crane moves left or right. Overall, it can be determined that when the crane rotates up a slope, whether it is from left or right, the slewing torque reaches the lowest values, and its value increases as the crane gets closer to the front of the machine (along the longitudinal axis of the machine). This change in the slewing torque is then characterized by a parabola. Furthermore, an effect was observed of the slewing gear slope on the lifting torque, which reached higher values in a tilted position than on a flat surface.

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“…In the framework of multibody system dynamics [35,46], a large number of studies have been presented that demonstrate coupling of multibody systems and hydraulic actuators [22,40]. Coupling has been carried out using either monolithic [48,49] or cosimulation approaches [44,47]. There are even studies using a monolithic approach that demonstrate this coupling for real-time applications, such as [6] and [31].…”

Section: Introductionmentioning

confidence: 99%

Efficiency comparison of various friction models of a hydraulic cylinder in the framework of multibody system dynamics

2021

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Dynamic simulation of mechanical systems can be performed using a multibody system dynamics approach. The approach allows to account systems of other physical nature, such as hydraulic actuators. In such systems, the nonlinearity and numerical stiffness introduced by the friction model of the hydraulic cylinders can be an important aspect to consider in the modeling because it can lead to poor computational efficiency. This paper couples various friction models of a hydraulic cylinder with the equations of motion of a hydraulically actuated multibody system in a monolithic framework. To this end, two static friction models, the Bengisu–Akay model and Brown–McPhee model, and two dynamic friction models, the LuGre model and modified LuGre model, are considered in this work. A hydraulically actuated four-bar mechanism is exemplified as a case study. The four modeling approaches are compared based on the work cycle, friction force, energy balance, and numerical efficiency. It is concluded that the Brown–McPhee approach is numerically the most efficient approach and it is well able to describe usual friction characteristics in dynamic simulation of hydraulically actuated multibody systems.

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On the cosimulation of multibody systems and hydraulic dynamics

Cited by 31 publications

References 34 publications

Energy-based monitoring and correction to enhance the accuracy and stability of explicit co-simulation

Energy-based monitoring and correction to enhance the accuracy and stability of explicit co-simulation

Verifying the Lifting and Slewing Dynamics of a Harvester Crane with Possible Levelling When Operating on Sloping Grounds

Efficiency comparison of various friction models of a hydraulic cylinder in the framework of multibody system dynamics

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