Automotive drivetrain model for transmission damage prediction

Foulard, Stéphane; Rinderknecht, Stephan; Ichchou, Mohamed; Perret-Liaudet, Joël

doi:10.1016/j.mechatronics.2015.06.008

Cited by 14 publications

(10 citation statements)

References 32 publications

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“…Orthogonality of a basis is established in function of an inner product definition. We take interest in the inner product defined in (3). A polynomial basis is orthogonal w.r.t.…”

Section: Generalized Polynomial Chaosmentioning

confidence: 99%

Inverse parametric uncertainty identification using polynomial chaos and high-order moment matching benchmarked on a wet friction clutch

et al. 2020

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A numerically efficient inverse method for parametric model uncertainty identification using maximum likelihood estimation is presented. The goal is to identify a probability model for a fixed number of model parameters based on a set of experiments. To perform maximum likelihood estimation, the output probability density function is required. Forward propagation of input uncertainty is established combining Polynomial Chaos and moment matching. High-order moments of the output distribution are estimated using the generalized Polynomial Chaos framework. Next, a maximum entropy parametric distribution is matched with the estimated moments. This method is numerically very attractive due to reduced forward sampling and deterministic nature of the propagation strategy. The methodology is applied on a wet clutch system for which certain model variables are considered as stochastic.The number of required model simulations to achieve the same accuracy as the brute force methodologies is decreased by one order of magnitude. The probability model identified with the high order estimates resulted into a true log-likelihood increase of about 4% since the accuracy of the estimated output probability density function could be improved up to 47%.

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“…Orthogonality of a basis is established in function of an inner product definition. We take interest in the inner product defined in (3). A polynomial basis is orthogonal w.r.t.…”

Section: Generalized Polynomial Chaosmentioning

confidence: 99%

Inverse parametric uncertainty identification using polynomial chaos and high-order moment matching benchmarked on a wet friction clutch

et al. 2020

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“…Due to the complexity of the analysed system, any analysis of the lifespan of the vehicle drivetrain requires a meticulous approach. Therefore, in the process of the development of a vehicle the measurements and simulation data must be combined; for instance, in that process the vehicle performance may be predicted fairly exactly, but a fatigue life estimation, as a result of a more complex analysis, permits only relative statements, and they are always supported by tests [23]. In that sense, [24] presents a system for the continual tracking of working conditions and the estimation of a remaining lifespan of automotive transmission gear wheels, while the model of a drive system and the damage of a gearwheel are presented in [25].…”

Section: Determination Of Loads and Estimation Of Lifespanmentioning

confidence: 99%

Analysis of the Influence of Pavement Irregularities on the Lifespan of a Vehicle’s Drive-Wheel Half Shaft

Simović

Popović

Damjanović

2016

SV-JME

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As a complex technical system, a vehicle requires a full analysis of its dynamic behaviour. A vehicle is the research subject requiring a detailed analysis of all separate systems both individually and in mutual interaction. One of the technical aspects of vehicle analysis is the lifespan of each element. This paper presents an analysis of the impact of the characteristics of pavement irregularities on the lifespan of a half shaft. In this paper, a mathematical model and a computer simulation of vehicle half-shaft loads have been set up. The importance of this approach is reflected in the use of state-of-the-art computational methods of analysis. The obtained results enable the drawing of clear conclusions about the effects of pavement properties on the lifespan of a vehicle half shaft.Keywords: vehicle, pavement, half shaft, load, lifespan Highlights • The influence of pavement irregularities on a vehicle drive-wheel half shaft is analysed. • A mathematical model of vehicle half-shaft loads has been set up and the influence on lifespan is analysed.• Simulation results of dynamic behaviour were tested and verified through experiments.• that when a model is simpler, it will possibly be less accurate, while a more complex model will be less suitable for the vehicle motion simulations. A detailed analysis of the wheel dynamics is usually done with the data obtained from the performed experimental investigations where the wheel-pavement contact is analysed and the conclusions about the particular characteristics were drawn, for example that the main parameters of the tyre influencing the generated force are the vertical and the radial stiffness of a tyre, where the pneumatic damping characteristic may be neglected, [13] to [15].The need to perform an analysis of a vehicle systems element lifespans is also clearly indicated. The importance of this analysis is proven by fact that a vehicle durability depends on design geometry, material properties, and load, with road roughness as an important parameter influencing the vehicle load. The analysis of the lifespan of vehicle drivetrain system elements in relation to the diversity of pavement characteristics shows that the design of vehicle systems should be adjusted to the vehicle exploitation condition, [10].Thus, different approaches in the process of solving certain problems in a lifespan analysis are used [16]. In the analysis of lifespan, the real conditions are usually replaced by the values of the estimated forces and stresses acting on the vehicle system elements [17] and [18]. The fatigue and reliability tests may be performed in terms of analysing different roads, analysing interacting influences of some mass and geometrical parameters of the vehicles or analysis of the relative fatigue damage of the drivetrain systems for specific roads [19] to [21]. DETERMINATION OF LOADS AND ESTIMATION OF LIFESPANThe analyses of vehicle elements' lifespan are usually conducted in terms of a service life and an analysis of the load of some vehicle elements. In this regard, an...

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“…A drivetrain model aimed for damage estimation purpose, exhaustively simulating dynamics events like engine cyclic irregularities, gearwheel stiffness variations, shift processes for different driver profiles, wheel dynamics, and tire grip loss, was developed [12]. An overview is proposed in Fig.…”

Section: Drivetrain and Damage Calculation Modelsmentioning

confidence: 99%

“…In the next sections, the model is intentionally not described in detail, and only the principle and main features are addressed. A deep description of the model can be found in [12].…”

Section: Drivetrain and Damage Calculation Modelsmentioning

confidence: 99%

Online and real-time monitoring system for remaining service life estimation of automotive transmissions – Application to a manual transmission

et al. 2015

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Automotive drivetrain model for transmission damage prediction

Cited by 14 publications

References 32 publications

Inverse parametric uncertainty identification using polynomial chaos and high-order moment matching benchmarked on a wet friction clutch

Inverse parametric uncertainty identification using polynomial chaos and high-order moment matching benchmarked on a wet friction clutch

Analysis of the Influence of Pavement Irregularities on the Lifespan of a Vehicle’s Drive-Wheel Half Shaft

Online and real-time monitoring system for remaining service life estimation of automotive transmissions – Application to a manual transmission

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