Estimation of Brake Friction Coefficient for Blending Function of Base Braking Control

Ricciardi, Vincenzo; Savitski, Dzmitry; Augsburg, Klaus; Ivanov, Valentin

doi:10.4271/2017-01-2520

Cited by 20 publications

(16 citation statements)

References 17 publications

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“…In that case the state observer would acquire vehicle states from existing vehicle sensors. This method was investigated by Ricciardi et al (2017), where a linear Kalman filter was used in concert with a Burckhardt tyre force model as a wheel torque observer. This system incorporated measurements from a chassis accelerometer that measured longitudinal and lateral acceleration of the vehicle; it also included measurements from wheel speed sensors.…”

Section: Vehicle State Observersmentioning

confidence: 99%

Estimation of tyre forces using smart tyre sensors and artificial intelligence

Bastiaan

2018

IJVD

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In-tyre strain measurements from a smart tyre sensor system are analysed using two artificial neural network types, in order to estimate tyre forces. A tyre finite element model is used to calculate in-tyre strain (inputs) and tyre forces developed at the wheel centre (outputs) for use in the neural networks. Neural networks are trained on pure slip conditions and tested on combined slip events with the goal of accurately predicting tyre longitudinal and lateral forces and the aligning moment. The large mapping function is fitted using multilayer perceptron and radial basis function networks. Results from the best radial basis function network design are excellent, with training times under one minute, testing times of milli-seconds and calculated tyre forces within 1%. The conclusion is that radial basis function networks can be used effectively for real time analysis of strain sensor measurements in a smart tyre sensor system.

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Section: Vehicle State Observersmentioning

confidence: 99%

Estimation of tyre forces using smart tyre sensors and artificial intelligence

Bastiaan

2018

IJVD

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“…The EHB system finds wide use in EV, because it ensures smooth coordination between conventional and regenerative brakes without the driver noticing it. When the driver steps on the brake pedal, the pedal stroke is measured, sent to the vehicle control unit (VCU) and converted into the reference vehicle deceleration level [15]. In turn, the VCU determines the total demanded braking torque and, according to the brake torque distribution rule, calculates the demanded brake pressure for each wheel.…”

Section: A Base Brake Controllermentioning

confidence: 99%

“…The parametrized vehicle model has been validated against experimental data collected at the Technische Universität Ilmenau (TU Ilmenau). Data from the brake dynamometric test rig [15] were exploited to reproduce the real dynamics of the brake linings coefficient of friction. Data collected from the EHB test rig at TU Ilmenau [16] were used to identify the model of the hydraulic brake circuit.…”

Section: B Vehicle Subsystemsmentioning

confidence: 99%

“…[8]: the models are incapable to rightly render the complex wear phenomena occurring in the contact zone and unreliable when the plant characteristics change due to brake wear itself or in case of replacement with aftermarket brake linings and owing to the variation in the weather conditions. The state observer proposed by the same authors in a previous work [15] has been herein employed for the estimation of the dissipated power in brakes and tires. The possibility to predict online the dissipated power in brakes and tires is an important feature for the estimation of wear and PM emissions.…”

Section: Estimation Of Power Dissipationmentioning

confidence: 99%

“…In this work, a novel approach for the estimation of the dissipated power in disc brakes and tires is presented. This latter draws upon a Kalman observer of the wheel torque as proposed in [15]. The developed tool encompasses the chassis and wheels' rotational dynamics and relies upon the wheel speed sensors and the inertia measurement unit by avoiding the analytical description of non-linear phenomena occurring in the pad-disc and tire-road contacts.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Estimation of Power Dissipation in Disc Brakes and Tires for Motion Control Applications in Electric Vehicles

Ricciardi

Ivanov

Augsburg

2018

IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

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The increasing widening of electric propulsion systems pushes the research world to focus on novel technologies aimed at reducing brake-and tire-related non-exhaust emissions. Hereunto, the Electro-Hydraulic Brake system (EHB) has gained particular importance among the control community owing to the necessity of developing more and more sophisticated control systems for the enhancement of brake blending and regenerative functions. The paper introduces a novel methodology based on the Kalman Filter theory for the estimation of the dissipated power in disc brakes and tires during vehicle deceleration events. This tool draws upon the wheel speed sensors and the inertia measurement unit (IMU). The functionality of the developed estimator is tested against simulation analysis performed under the proprietary software IPG CarMaker®. Novel control systems could use this tool to enhance the vehicle performance and to simultaneously reduce the non-exhaust emissions.

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Blended Antilock Braking System Control Method for All-Wheel Drive Electric Sport Utility Vehicle

Aksjonov

Vodovozov

Augsburg

et al. 2020

Lecture Notes in Electrical Engineering

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At least two different actuators work in cooperation in regenerative braking for electric and hybrid vehicles. Torque blending is an important area, which is responsible for better manoeuvrability, reduced braking distance, improved riding comfort, etc. In this paper, a control method for electric vehicle blended antilock braking system based on fuzzy logic is promoted. The principle prioritizes usage of electric motor actuators to maximize recuperation energy during deceleration process. Moreover, for supreme efficiency it considers battery's state of charge for switching between electric motor and conventional electrohydraulic brakes. To demonstrate the functionality of the controller under changing dynamic conditions a hardware-in-the-loop simulation with real electrohydraulic brakes test bed is utilized. In particular, the experiment is designed to exceed the state of charge threshold during braking operation, what leads to immediate switch between regenerative and friction brake modes. ELECTRIMACS2019, 027, v2 (final): 'Blended antilock braking system control method. . .

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Estimation of Brake Friction Coefficient for Blending Function of Base Braking Control

Cited by 20 publications

References 17 publications

Estimation of tyre forces using smart tyre sensors and artificial intelligence

Estimation of tyre forces using smart tyre sensors and artificial intelligence

Estimation of Power Dissipation in Disc Brakes and Tires for Motion Control Applications in Electric Vehicles

Blended Antilock Braking System Control Method for All-Wheel Drive Electric Sport Utility Vehicle

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