Intelligent control for ABS application with identification of road and environmental properties

Ivanov, Valentin; Algin, V.B.; Shyrokau, Barys

doi:10.1504/ijvas.2006.009307

Cited by 7 publications

(6 citation statements)

References 7 publications

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“…Similar to the previous work, other FLCs have frequently been proposed to tackle the problem of ABS for the unknown environmental parameters [44], [45]. The large number of the fuzzy rules, however, makes the analysis comparable to the threshold controllers' case in terms of complexity.…”

Section: B Fuzzy Logic Controllers (Flc)mentioning

confidence: 97%

Survey on Wheel Slip Control Design Strategies, Evaluation and Application to Antilock Braking Systems

et al. 2020

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Since their introduction, anti-lock braking systems (ABS) have mostly relied on heuristic, rule-based control strategies. ABS performance, however, can be significantly improved thanks to many recent technological developments. This work presents an extensive review of the state of the art to verify such a statement and quantify the benefits of a new generation of wheel slip control (WSC) systems. Motivated by the state of the art, as a case study, a nonlinear model predictive control (NMPC) design based on a new load-sensing technology was developed. The proposed ABS was tested on Toyota's high-end vehicle simulator and was benchmarked against currently applied industrial controller. Additionally, a comprehensive set of manoeuvres were deployed to assess the performance and robustness of the proposed NMPC design. The analysis showed substantial reduction of the braking distance and better steerability with the proposed approach. Furthermore, the proposed design showed comparable robustness against external factors to the industrial benchmark. INDEX TERMS Road vehicles, vehicle safety, antilock braking system, wheel slip control, model predictive control.

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Section: B Fuzzy Logic Controllers (Flc)mentioning

confidence: 97%

Survey on Wheel Slip Control Design Strategies, Evaluation and Application to Antilock Braking Systems

et al. 2020

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“…Description of output variable for FIS "Environment" legend: 1 -ultra highly wet road (aquaplaning tendency), 2 -wet ice, 3 -ice by "about zero" temperature, 4 -pressed snow, ice by frost, 5 -contaminated snow, highly contaminated road, 6 -contaminated road, 7 -highly wet concrete, 8 -highly wet asphalt, 9 -wet asphalt/concrete, 10 -slightly wet concrete, 11 -slightly wet asphalt, 12 -dry concrete, 13 -heated dry asphalt, 14 -dry asphalt, 15 -enhanced dry asphalt, 16 -dry road with environmentally-related enhanced friction. control logic were discussed in the previous works of authors [31]. Fig.…”

Section: Example Of Fuzzy Road Identification For Vehicle Dynamics Comentioning

confidence: 97%

“…Thus, this task can be achieved through a set of sensors that assess the road surface texture, temperature, moisture, and intensity of precipitation. This approach is the development of the authors' research set out in [30][31][32]. The relevant observer has to evaluate the friction coefficient on the basis of informational parameters listed here and may transmit the received value for subsequent use in vehicle control systems.…”

Section: Choice Of Information Spacementioning

confidence: 99%

Fuzzy evaluation of tyre–surface interaction parameters

Ivanov

Shyrokau

Augsburg

et al. 2010

Journal of Terramechanics

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“…In (Castillo et al, 2016), a road type was detected by Kalman filter, FLC, and artificial neural network models combination. In (Ivanov et al, 2006), road surface was estimated using eight variables applying three different FLCs. Lastly, another intelligent ABS FLC was described in (Aly, 2010), where three different FLCs (i.e.…”

Section: Discussionmentioning

confidence: 99%

“…Advanced FLCs for road type detection and thus optimal braking pressure generation were designed in (Ivanov et al, 2006;Aly, 2010;Castillo et al, 2016). Although the experimental results showed perfect performance on varying road surfaces, the control algorithms are very complex.…”

Section: Related Workmentioning

confidence: 99%

Design of Regenerative Anti-Lock Braking System Controller for 4 In-Wheel-Motor Drive Electric Vehicle with Road Surface Estimation

Aksjonov

Vodovozov

Augsburg

et al. 2018

Int.J Automot. Technol.

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This paper presents a regenerative anti−lock braking system control method with road detection capability. The aim of the proposed methodology is to improve electric vehicle safety and energy economy during braking maneuvers. Vehicle body longitudinal deceleration is used to estimate a road surface. Based on the estimation results, the controller generates an appropriate braking torque to keep an optimal for various road surfaces wheel slip and to regenerate for a given motor the maximum possible amount of energy during vehicle deceleration. A fuzzy logic controller is applied to fulfill the task. The control method is tested on a four in−wheel−motor drive sport utility electric vehicle model. The model is constructed and parametrized according to the specifications provided by the vehicle manufacturer. The simulation results conducted on different road surfaces, including dry, wet and icy, are introduced.

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Intelligent control for ABS application with identification of road and environmental properties

Cited by 7 publications

References 7 publications

Survey on Wheel Slip Control Design Strategies, Evaluation and Application to Antilock Braking Systems

Survey on Wheel Slip Control Design Strategies, Evaluation and Application to Antilock Braking Systems

Fuzzy evaluation of tyre–surface interaction parameters

Design of Regenerative Anti-Lock Braking System Controller for 4 In-Wheel-Motor Drive Electric Vehicle with Road Surface Estimation

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