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Robust brake linings friction coefficient estimation for enhancement of ehb control

Authors: Vincenzo Ricciardi; Manuel Acosta; Klaus Augsburg; Stratis Kanarachos; Valentin G. Ivanov;

Robust brake linings friction coefficient estimation for enhancement of ehb control

Abstract

The latest braking system architectures for Hybrid (HEV) and Full Electric Vehicles (EV) feature the adoption of the X-by-wire solutions, namely electro-hydraulic (EHB) and electro-mechanical (EMB) braking systems, aimed at providing additional flexibility to the distinctive functions of brake blending and regeneration. Regenerative brakes still need to be supported by conventional friction brakes because of failures occurrence, fully-charged battery conditions, and unexpected variations of the tire-road friction coefficient. In order to achieve a smooth coordinated action between the regenerative and the conventional friction brakes, the brake linings coefficient of friction (BLCF) needs to be monitored. The main contribution of this work lies on the estimation of the BLCF using a tire-model-less approach. In particular, two different observer designs are proposed and compared. Whereas the proposed approach does not rely on any fixed tire modelization, the state estimation is robust against variations in the road friction characteristics and tire uncertainties caused by inflating pressure variations, wear, and aging. The functionality of the developed observers is tested in IPG CarMaker® by employing an experimentally validated EV, equipped with four onboard motors and an EHB system. Braking events are simulated at different deceleration levels on both dry and wet surfaces. Finally, the compensation function against variations in the BLCF is implemented in the EHB controller to achieve constant deceleration levels. Authors envisage that the precise knowledge of the BLCF will contribute to enhance the braking performance and to actively monitor the brake pad wear under different working conditions.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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