Model andcontrol of vehicle dynamics and monitoring of attitude and performance

Authors

  • Matheus José Oliveira dos Santos Dias Sem registro de afiliação

DOI:

https://doi.org/10.11606/issn.2526-8260.mecatrone.2023.220754

Keywords:

Dynamics, Optimal Control, Monitoring, Railroad Vehicles

Abstract

This text begins with the statement of the problem and the objective of proposing a method of controlling and monitoring vehicles on rails in order to improve the safety of the railroad car against overturning. With that in mind, the vehicle was
modeled using principles of Newton-Euler and Lagrangian mechanics, the model represents the lateral dynamics of the train. With the model in hand, the system is studied by observing its behavior in the time and frequency domains, making it possible to
identify their respective natural frequencies and normal modes. To solve the monitoring problem, an application was developed with MIT App Inventor with the intention of taking advantage of the IMU chip present in all modern smartphones. The application
manages to save the information in the device's memory and then export the gyroscope and accelerometer signals, with these signals it is possible to use a complementary filter to measure the roll angle with greater precision. Therefore, with the dynamic model and the monitoring system, an LQR control system is proposed with two electromagnetic actuators acting on the railroad car and bogie, laterally, in order to keep the car roll angle controlled, avoiding overturning of the train. The controlled system is then evaluated at steady state during a curve and the results are discussed.

Downloads

Download data is not yet available.

Author Biography

  • Matheus José Oliveira dos Santos Dias, Sem registro de afiliação

    Formado em engenharia mecânica com ênfase em aeronáutica pela Escola Politécnica da Universidade de São Paulo, possui experiência com modelagem matemática e física de problemas de engenharia, ciência da computação, construção de protótipos e desenvolvimento de produto. Trabalha a mais de 3 anos com Engenharia de Software, realizando desenvolvimento e manutenção de softwares escaláveis com código limpo, em especial sistemas para engenharia de dados e engenharia de Machine Learning.

References

AHMAD N.; GHAZILLA, R.A.R; KHAIRI N.M. Reviews on Various Inertial Measurement Unit (IMU) Sensor Applications. Dept. Of Electrical Engineering, University of Malaya. International Journal of Signal Processing Systems Vol. 1, No. 2 December 2013.

ANDERSON, R.T., BARKAN, C.P. Derailment Probability Analyses and Modeling of Mainline Freight Trains. Inproc., 8Th International Heavy Haul Railway Conference, Rio de Janeiro, Brasil, jun. 2005.

ANTF (org.). Densidade das Malhas Ferroviárias, 2018. Disponível em: https://www.antf.org.br/informacoes-gerais/attachment/densidade-da-malha-ferroviaria/. Acesso em: 17 jun. 2022.

ANTUNES, C. Geografia do Brasil. São Paulo: Scipione, 1993.

APARNA, G.J; KAMAL, C.; RAJESH, N.M. IMU Based Attitude Estimation Using Adaptative Complementary Filter. IEEE International Conference on Communication information and Computing Technology (ICCICT), 2021, pp. 1-5, doi: 10.1109/ICCICT50803.2021.9510153.

BARBOSA, R.S. Notas de aula: Equações dinâmicas de Movimento espacial para corpos rígidos utilizando um referencial móvel. Escola Politécnica da Universidade de São Paulo – Departamento de Engenharia Mecânica, São Paulo, [201-].

BARBOSA, R.S. Aplicação de Sistemas Multicorpos na Dinâmica de Veículos Guiados. Tese (Doutorado em Engenharia Mecânica). Universidade de São Paulo – Escola de Engenharia de São Carlos. 1999.

BARBOSA, R.S. Notas de aula: Dinâmica Veicular – Quatro GL Excitação pela base. Escola Politécnica da Universidade de São Paulo – Departamento de Engenharia Mecânica.

CAMPOS NETO, Carlos Alvares da Silva. Reflexões sobre Investimentos em Infraestrutura de Transporte no Brasil. Instituto de Pesquisa Econômica Aplicada. Brasilia, 2016. CSX (org.). Railroad Equipment. Disponível em:

<https://www.csx.com/index.cfm/customers/resources/equipment/railroad-equipment/>. Acesso em: 17 set. 2022.

GOOGLE. Google Maps. 2023. Disponível em: https://www.google.com/maps. Acesso em: 31 fev. 2023.

KING. A.D. Inertial Navigation - Forty Years of Evolution. 140 GEC REVIEW, Vol. 13, No. 3, 1998.

MATLAB (org.). Accelerometer. Disponível em: https://www.mathworks.com/help/supportpkg/android/ref/accelerometer.html. Acesso em: 19 nov. 2022.

MIT App Inventor Lista de Tutoriais para desenvolver aplicações. Disponível em <https://appinventor.mit.edu/explore/ai2/tutorials>. Acesso em 1 de Maio de 2022.

PARK, J. et al. A practical approach to active lateral suspension for railway vehicles. Measurement And Control, [s. l], v. 52, n. 9-10, p. 1195-1209, nov. 2019.

RAMALHO, P.R.A.M. O novo marco regulatório das ferrovias brasileiras. Disponível em: https://www.gov.br/infraestrutura/pt-br/assuntos/conjur/o-novo-marco-regulatorio-das-ferrovias-brasileiras. Acesso em: 17 jun. 2022.

RAO, S.S. Mechanical Vibrations 5th ed. University of Miami. 2004.

OGATA, Katsuhiko. Modern Control Engineering. 5. ed. New Jersey: Pearson, 2010.

Published

2023-12-29

Issue

Section

Artigos

How to Cite

Model andcontrol of vehicle dynamics and monitoring of attitude and performance. (2023). Mecatrone, 6(1), 1-21. https://doi.org/10.11606/issn.2526-8260.mecatrone.2023.220754