Longitudinal wheel slip control using dynamic neural networks
Само за регистроване кориснике
2013
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
The control of automotive braking systems performance and a wheel slip is a challenging problem due to nonlinear dynamics of a braking process and a tire-road interaction. When the wheel slip is not between the optimal limits during braking, the desired tire-road friction force cannot be achieved, which influences braking distance, the loss in steerability and maneuverability of the vehicle. In this paper, the new approach, based on dynamic neural networks, has been employed for improving of the longitudinal wheel slip control. This approach is based on dynamic adaptation of the brake actuation pressure, during a braking cycle, according to the identified maximum adhesion coefficient between the wheel and road. The brake actuated pressure was adjusted on the level which provides the optimal longitudinal wheel slip versus the brake actuated pressure selected by a driver, the current vehicle speed, load conditions, the brake interface temperature and the current value of the wheel slip. ...The dynamic neural network has been used for modeling of a nonlinear functional relationship between the brake actuation pressure and the longitudinal wheel slip during a braking cycle. It provided preconditions for control of the brake actuation pressure based on the wheel slip change.
Кључне речи:
Wheel slip / Neural network control / Commercial vehiclesИзвор:
Mechatronics, 2013, 23, 1, 135-146Издавач:
- Pergamon-Elsevier Science Ltd, Oxford
Финансирање / пројекти:
- Научно-технолошка подршка унапређењу безбедности специјалних друмских и шинских возила (RS-35045)
- Развој, пројектовање и имплементација савремених стратегија интегрисаног управљања оперативним радом и одржавањем возила и механизације у системима аутотранспорта, рударства и енергетике (RS-35030)
DOI: 10.1016/j.mechatronics.2012.11.007
ISSN: 0957-4158
WoS: 000314857300012
Scopus: 2-s2.0-84901840227
Колекције
Институција/група
Mašinski fakultetTY - JOUR AU - Ćirović, Velimir AU - Aleksendrić, Dragan AU - Smiljanić, Dušan PY - 2013 UR - https://machinery.mas.bg.ac.rs/handle/123456789/1655 AB - The control of automotive braking systems performance and a wheel slip is a challenging problem due to nonlinear dynamics of a braking process and a tire-road interaction. When the wheel slip is not between the optimal limits during braking, the desired tire-road friction force cannot be achieved, which influences braking distance, the loss in steerability and maneuverability of the vehicle. In this paper, the new approach, based on dynamic neural networks, has been employed for improving of the longitudinal wheel slip control. This approach is based on dynamic adaptation of the brake actuation pressure, during a braking cycle, according to the identified maximum adhesion coefficient between the wheel and road. The brake actuated pressure was adjusted on the level which provides the optimal longitudinal wheel slip versus the brake actuated pressure selected by a driver, the current vehicle speed, load conditions, the brake interface temperature and the current value of the wheel slip. The dynamic neural network has been used for modeling of a nonlinear functional relationship between the brake actuation pressure and the longitudinal wheel slip during a braking cycle. It provided preconditions for control of the brake actuation pressure based on the wheel slip change. PB - Pergamon-Elsevier Science Ltd, Oxford T2 - Mechatronics T1 - Longitudinal wheel slip control using dynamic neural networks EP - 146 IS - 1 SP - 135 VL - 23 DO - 10.1016/j.mechatronics.2012.11.007 ER -
@article{ author = "Ćirović, Velimir and Aleksendrić, Dragan and Smiljanić, Dušan", year = "2013", abstract = "The control of automotive braking systems performance and a wheel slip is a challenging problem due to nonlinear dynamics of a braking process and a tire-road interaction. When the wheel slip is not between the optimal limits during braking, the desired tire-road friction force cannot be achieved, which influences braking distance, the loss in steerability and maneuverability of the vehicle. In this paper, the new approach, based on dynamic neural networks, has been employed for improving of the longitudinal wheel slip control. This approach is based on dynamic adaptation of the brake actuation pressure, during a braking cycle, according to the identified maximum adhesion coefficient between the wheel and road. The brake actuated pressure was adjusted on the level which provides the optimal longitudinal wheel slip versus the brake actuated pressure selected by a driver, the current vehicle speed, load conditions, the brake interface temperature and the current value of the wheel slip. The dynamic neural network has been used for modeling of a nonlinear functional relationship between the brake actuation pressure and the longitudinal wheel slip during a braking cycle. It provided preconditions for control of the brake actuation pressure based on the wheel slip change.", publisher = "Pergamon-Elsevier Science Ltd, Oxford", journal = "Mechatronics", title = "Longitudinal wheel slip control using dynamic neural networks", pages = "146-135", number = "1", volume = "23", doi = "10.1016/j.mechatronics.2012.11.007" }
Ćirović, V., Aleksendrić, D.,& Smiljanić, D.. (2013). Longitudinal wheel slip control using dynamic neural networks. in Mechatronics Pergamon-Elsevier Science Ltd, Oxford., 23(1), 135-146. https://doi.org/10.1016/j.mechatronics.2012.11.007
Ćirović V, Aleksendrić D, Smiljanić D. Longitudinal wheel slip control using dynamic neural networks. in Mechatronics. 2013;23(1):135-146. doi:10.1016/j.mechatronics.2012.11.007 .
Ćirović, Velimir, Aleksendrić, Dragan, Smiljanić, Dušan, "Longitudinal wheel slip control using dynamic neural networks" in Mechatronics, 23, no. 1 (2013):135-146, https://doi.org/10.1016/j.mechatronics.2012.11.007 . .