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Foulard, Stéphane
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Stochastic Synthesis of Representative and Multidimensional Driving Cycles

SAE International Journal of Alternative Powertrains

COMPREDICT-Martin Zeller, Stéphane Foulard
TU Darmstadt-Arved Esser, Stephan Rinderknecht
  • Journal Article
  • 2018-01-0095
Published 2018-04-03 by SAE International in United States
Driving cycles play a fundamental role in the design of components, in the optimization of control strategies for drivetrain topologies, and in the identification of vehicle properties. The focus on a single or a few test cycles results in a risk of non-optimal or even poor design regarding the real usage profiles. Ideally, multiple different driving cycles that are representative of the real and scattering operating conditions are used. Therefore, tools for the stochastic generation of representative driving cycles are required, and many works have addressed this issue with different approaches. Until now, the stochastic generation of representative testing cycles has been limited to low dimensionality, and only a few works have studied higher dimensionality using Markov chain theory. However, it is mandatory to create tools that can stochastically generate multidimensional cycles incorporating all relevant operating conditions and maintaining signal dependency at the same time. For this purpose, a new method to synthesize multidimensional and representative testing cycles that can handle constraints and is suited for many evaluation criteria is presented in this study. The…
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Vehicle Mass Estimation from CAN Data and Drivetrain Torque Observer

Politecnico di Torino-Jyotishman Ghosh
TU Darmstadt-Stéphane Foulard, Rafael Fietzek
Published 2017-03-28 by SAE International in United States
A method for estimating the vehicle mass in real time is presented. Traditional mass estimation methods suffer due a lack of knowledge of the vehicle parameters, the road surface conditions and most importantly the effect of the vehicle transmission. To resolve these issues, a method independent of a vehicle model is utilized in conjunction with a drivetrain output torque observer to obtain the estimate of the vehicle mass. Simulations and experimental track tests indicate that the method is able to accurately estimate the vehicle mass with a relatively fast rate of convergence compared to traditional methods.
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Online and Real-Time Condition Prediction for Transmissions based on CAN-Signals

TU Darmstadt-Stephan Rinderknecht, Rafael Fietzek, Stéphane Foulard
Published 2017-03-28 by SAE International in United States
An online and real-time Condition Prediction system, so-called lifetime monitoring system, was developed at the Institute for Mechatronic Systems in Mechanical Engineering (IMS) of the TU Darmstadt, which is intended for implementation in standard control units of series production cars. Without additional hardware and only based on sensors and signals already available in a standard car, the lifetime monitoring system aims at recording the load/usage profiles of transmission components in aggregated form and at estimating continuously their remaining useful life. For this purpose, the dynamic transmission input and output torques are acquired realistically through sensor fusion.In a further step, the lifetime monitoring system is used as an input-module for the introduction of innovative procedures to more load appropriate dimensioning, cost-efficient lightweight design, failure-free operation and predictive maintenance of transmissions. This is based on damage-oriented operating strategies (so-called eLIFE) and a paradigm shift in the design philosophy relying on a smart big data approach (so-called ecoLIFE3 design procedure).The paper will present the lifetime monitoring system by the example of two concrete application cases, namely a manual…
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