The Experts below are selected from a list of 26829 Experts worldwide ranked by ideXlab platform
Tim Kratzer - One of the best experts on this subject based on the ideXlab platform.
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Virtual verification of automotive Steering Systems
Proceedings, 2017Co-Authors: Matthijs Klomp, Ramadan Salif, Michael Attinger, Steven Hoesli, Holger Bleicher, Marcus Ljungberg, Tim KratzerAbstract:The vehicle industry is in a transformation where software and electronics are revolutionizing the way we engineer the cars of the future. This is particularly true for Steering Systems, which have developed from passive mechanical Systems to now enabling advanced driver support Systems and the evolution toward fully autonomous driving. With this ever increasing complexity, relying only on physical testing is no longer practical due to slow feedback loops from testing back to development and the lack of repeatability. The question addressed in this paper is how computational methods can help to increase test coverage, shorten development cycles and enable continuous integration of software for Steering Systems. In particular the development, validation and application of methods to virtually release Steering Systems for passenger vehicles is presented.
Kazusa Yamamoto - One of the best experts on this subject based on the ideXlab platform.
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Design and experimentation of an LPV extended state feedback control on Electric Power Steering Systems
Control Engineering Practice, 2019Co-Authors: Kazusa Yamamoto, Olivier Sename, Damien Koenig, Pascal MoulaireAbstract:This paper deals with Column-type Electric Power Steering Systems. An state feedback Linear Parameter-Varying controller is developed considering a parameter-dependent Lyapunov function. For practical implementation, an Proportional Integral observer is added for state and driver torque estimation. The whole observer-based control has been implemented in real-time using dSpace/MicroAutobox on a test car. Some driving tests have been carried out on a test track, and promising results are achieved regarding both estimation and control performances.
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Control of electromechanical Systems, application on electric power Steering Systems
2017Co-Authors: Kazusa YamamotoAbstract:Nowadays, modern vehicles are equipped with more and more driving assistance Systems, among them Electric Power Steering (EPS) helps the driver to turn the wheels. Indeed, EPS provides through an electric motor, an additional torque according to the driver's behaviour and the vehicle's dynamics to reduce the amount of effort required to the driver. Therefore, a torque control is developed based on the torque sensor signal which measures in practice the torsion bar torque (corresponding to an image of the driver torque). Consequently, this component is essential to the functioning of EPS Systems.Indeed, a torque sensor failure usually leads to shut-off the assistance which may increase the risk of accident. Regarding functional safety, a back-up mode is recommended and required by more and more car manufacturers. On the other hand, a major challenge for automotive suppliers is to reduce cost production in order to meet growing markets demands and manage in the competitive sector. This issue considering a reduction of sensors' numbers and analysis of vehicle's dynamics is therefore an extension of applying the safety strategy. This thesis, carried out within JTEKT Europe, addresses these various issues.After introducing an overview of the different EPS Systems, some models used for the design of controllers and estimators are presented. Then, two methods to estimate the driver torque subject to road disturbances and noise measurements are proposed: the first is a proportional integral observer (PI) with mixed synthesis $H_infty / H_2 $, whereas the second is an $ H_infty $ filtering approach. Then, several control strategies are proposed according to two different cases, either by using a PI observer which estimates the system states and the driver torque (LQR, LPV feedback control) or by not taking into account the driver torque estimation ($ H_infty $dynamic output feedback control). This latter approach has the advantage to require less measurements than the previous one. These approaches have been validated in simulation and implemented on a prototype vehicle where promising results have been obtained.
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Control of electromechanical Systems, application on electric power Steering Systems
2017Co-Authors: Kazusa YamamotoAbstract:Nowadays, most vehicles are equipped with Electric Power Steering (EPS)system, which helps the driver to turn the wheels. Indeed, EPS provides through an electricmotor, an additional torque according to the driver's behaviour and the vehicle's dynamics toreduce the amount of effort required by the driver. Therefore, a torque control is commonlydeveloped, based on the torque sensor signal which measures in practice the torsion bar torque(an image of the applied driver torque). However, a failure of this sensor, essential to thefunctioning of EPS, usually leads to shut-off the assistance. Regarding functional safety, abackup mode is often required by car manufacturers. Besides, reducing EPS production costsremains a major challenge in the competitive OEM sector. This issue is considered as anextension, since the strategy does not use the torque sensor signal anymore. In this framework,some methods to estimate the driver torque are proposed, as well as the design of EPS controlsubject to specifc objectives. These different approaches have been validated in simulationand also implemented on a prototype vehicle, where promising results are obtained.
Riender Happee - One of the best experts on this subject based on the ideXlab platform.
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the effect of Steering system linearity simulator motion and truck driving experience on Steering of an articulated tractor semitrailer combination
Applied Ergonomics, 2018Co-Authors: Barys Shyrokau, Jan J Loof, Olaf Stroosma, Rene Van Paassen, Chris Dijksterhuis, Joost C F De Winter, Riender HappeeAbstract:Abstract Steering Systems of trucks consist of many linkages, which introduce nonlinearities that may negatively affect Steering performance. Nowadays, it is possible to equip Steering Systems with actuators that provide artificial Steering characteristics. However, before new Steering Systems are deployed in real vehicles, evaluation in a safe and controlled simulator environment is recommended. A much-debated question is whether experiments need to be performed in a motion-base simulator or whether a fixed-base simulator suffices. Furthermore, it is unknown whether simulator-based tests can be validly conducted with a convenience sample of university participants who have not driven a truck before. We investigated the effect of Steering characteristic (i.e., nonlinear vs. linear) on drivers' subjective opinions about the ride and the Steering system, and on their objective driving performance in an articulated tractor-semitrailer combination. Thirty-two participants (12 truck drivers and 20 university drivers) each completed eight 5.5-min drives in which the simulator's motion system was either turned on or off and the Steering model either resembled a linear (i.e., artificial) or nonlinear (i.e., realistic) system. Per drive, participants performed a lane-keeping task, merged onto the highway, and completed four overtaking manoeuvers. Results showed that the linear Steering system yielded less subjective and objective Steering effort, and better lane-keeping performance, than the nonlinear system. Consistent with prior research, participants drove a wider path through curves when motion was on compared to when motion was off. Truck drivers exhibited higher Steering activity than university drivers, but there were no significant differences between the two groups in lane keeping performance and Steering effort. We conclude that for future truck Steering Systems, a linear system may be valuable for improving performance. Furthermore, the results suggest that on-centre evaluations of Steering Systems do not require a motion base, and should not be performed using a convenience sample of university students.
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the influence of motion and Steering system model complexity on truck Steering
DSC 2016 Europe : Driving Simulation Conference & Exhibition Paris France 7-9 September 2016, 2016Co-Authors: Barys Shyrokau, Jan J Loof, Olaf Stroosma, Chris Dijksterhuis, Riender HappeeAbstract:Motion and Steering feel contribute to the drivers perception and assessment of vehicle behavior. Steer-by-wire Systems offer the freedom to alter the Steering feel characteristics. It is unknown whether the mechanical complexity and non-linearity in mechanical Steering Systems contribute to the performance and awareness of drivers. This study investigates the influence of driving simulator motion and Steering-system model complexity on drivers’ performance and subjective assessment of on-centre handling in a heavy goods vehicle. 32 subjects (12 professional truck drivers and 20 university participants) completed a total of eight short experimental highway rides including merging, while the simulator’s motion system was either turned on or off and the Steering system model either resembled a linear or a realistic nonlinear behavior. The results show that a linear Steering system is preferred by the drivers and no performance degradation occurs with the linear system, indicating that for future truck Steering Systems, a linear haptic feedback may be considered. The presence of motion did not significantly alter this result.
Matthijs Klomp - One of the best experts on this subject based on the ideXlab platform.
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an approach to develop haptic feedback control reference for Steering Systems using open loop driving manoeuvres
Vehicle System Dynamics, 2019Co-Authors: Tinkle Chugh, Fredrik Bruzelius, Matthijs Klomp, Barys ShyrokauAbstract:AbstractIn this paper, a methodology to capture the model-based haptic feedback control reference for closed-loop Steering Systems is demonstrated. The parameterisation is based on the measurements...
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Virtual verification of automotive Steering Systems
Proceedings, 2017Co-Authors: Matthijs Klomp, Ramadan Salif, Michael Attinger, Steven Hoesli, Holger Bleicher, Marcus Ljungberg, Tim KratzerAbstract:The vehicle industry is in a transformation where software and electronics are revolutionizing the way we engineer the cars of the future. This is particularly true for Steering Systems, which have developed from passive mechanical Systems to now enabling advanced driver support Systems and the evolution toward fully autonomous driving. With this ever increasing complexity, relying only on physical testing is no longer practical due to slow feedback loops from testing back to development and the lack of repeatability. The question addressed in this paper is how computational methods can help to increase test coverage, shorten development cycles and enable continuous integration of software for Steering Systems. In particular the development, validation and application of methods to virtually release Steering Systems for passenger vehicles is presented.
Shankar Sastry - One of the best experts on this subject based on the ideXlab platform.
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nonholonomic motion planning Steering using sinusoids
IEEE Transactions on Automatic Control, 1993Co-Authors: Richard M Murray, Shankar SastryAbstract:Methods for Steering Systems with nonholonomic c.onstraints between arbitrary configurations are investigated. Suboptimal trajectories are derived for Systems that are not in canonical form. Systems in which it takes more than one level of bracketing to achieve controllability are considered. The trajectories use sinusoids at integrally related frequencies to achieve motion at a given bracketing level. A class of Systems that can be steered using sinusoids (claimed Systems) is defined. Conditions under which a class of two-input Systems can be converted into this form are given. >
