Design of System and Components - NVH view - Test and Simulation

Oliveira, André de; Fiorentin, Thiago Antonio; Silva, Marcelo G.

doi:10.4271/2008-36-0239

Cited by 7 publications

(2 citation statements)

References 1 publication

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“…The literature offers solutions for cars, aircraft, electrical systems and others (Fiorentin et al 2013(Fiorentin et al , 2016Oliveira et al 2008). There are, also, some solutions that can be applied to railways, but they are expensive and need to be customized for each railroad.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Characterization of Noise Generated in Heavy-Haul Railways in Brazil

Fiorentin

Asaff

Braz

2021

Sustainable Rail Transport 4

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The noise generated by transportation systems is one of the most important causes of noise-induced annoyance, since exposure to high level noises for long periods of time can be detrimental to health. Amongst the different types of noise that originate from railroads, the squeal noise generated at curves, the impact noise generated at rail joints and the rolling noise stand out. To propose mitigation measures to this problem, noise generation must be understood as well as by which parameters it is influenced. To that end, analytical models have been developed to predict the generated Sound Pressure Level (SPL) and to verify which factors are related to noise generation. This paper aims to validate analytical models for impact noise, squeal noise and rolling noise, which were originally designed for urban railways, used for passenger transportation. In this work, the validation is made using SPL measurements taken at a Brazilian heavy-haul railway, and a railway which carries bulk cargo in general. The models are implemented on a numerical computation software considering vehicle and track characteristics, train speed and a reference SPL. The results obtained from the models were compared with SPL measurements performed at the railroad during regular operation for the three cases (rolling, squeal and impact), which, despite the measurement limitations imposed by practical constraints during regular traffic operation, showed good agreement.

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Section: Introductionmentioning

confidence: 99%

Analysis and Characterization of Noise Generated in Heavy-Haul Railways in Brazil

Fiorentin

Asaff

Braz

2021

Sustainable Rail Transport 4

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“…Nowadays, the car market is very competitive. Consumers are increasingly looking for efficient, comfortable, and safe vehicles [2][3][4]. To assist the driver, many safety functions have been developed, namely, autonomous emergency braking (AEB), electronic stability control (ESC), adaptive cruise control (ACC), and many others.…”

Section: Introductionmentioning

confidence: 99%

Actor-Critic Traction Control Based on Reinforcement Learning with Open-Loop Training

Drechsler

Fiorentin

Göllinger

2021

Modelling and Simulation in Engineering

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The use of actor-critic algorithms can improve the controllers currently implemented in automotive applications. This method combines reinforcement learning (RL) and neural networks to achieve the possibility of controlling nonlinear systems with real-time capabilities. Actor-critic algorithms were already applied with success in different controllers including autonomous driving, antilock braking system (ABS), and electronic stability control (ESC). However, in the current researches, virtual environments are implemented for the training process instead of using real plants to obtain the datasets. This limitation is given by trial and error methods implemented for the training process, which generates considerable risks in case the controller directly acts on the real plant. In this way, the present research proposes and evaluates an open-loop training process, which permits the data acquisition without the control interaction and an open-loop training of the neural networks. The performance of the trained controllers is evaluated by a design of experiments (DOE) to understand how it is affected by the generated dataset. The results present a successful application of open-loop training architecture. The controller can maintain the slip ratio under adequate levels during maneuvers on different floors, including grounds that are not applied during the training process. The actor neural network is also able to identify the different floors and change the acceleration profile according to the characteristics of each ground.

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Transmission characteristics and mechanism study of hydrodynamic and acoustic pressure through a side window of DrivAer model based on modal analytical approach

Wan

Liu

et al. 2021

Journal of Sound and Vibration

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Design of System and Components - NVH view - Test and Simulation

Cited by 7 publications

References 1 publication

Analysis and Characterization of Noise Generated in Heavy-Haul Railways in Brazil

Analysis and Characterization of Noise Generated in Heavy-Haul Railways in Brazil

Actor-Critic Traction Control Based on Reinforcement Learning with Open-Loop Training

Transmission characteristics and mechanism study of hydrodynamic and acoustic pressure through a side window of DrivAer model based on modal analytical approach

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