Abstract:The increased use of disc brakes in passenger cars has led the research world to focus on the prediction of brake performance and wear under different working conditions. A proper model of the brake linings' coefficient of friction (BLCF) is important to monitor the brake operation and increase the performance of control systems such as ABS, TC and ESP by supplying an accurate estimate of the brake torque. The literature of the last decades is replete with semi-empirical and analytical friction models whose derivation comes from significant research that has been conducted into the direction of friction modelling of pin-disc couplings. On the contrary, just a few models have been developed and used for the prediction of the automotive BLCF without obtaining satisfactory results. The present work aims at collecting the current state of art of the estimation techniques for the BLCF, with special attention to the models for automotive brakes. Moreover, the work proposes a classification of the several existing approaches and discusses the relative pro and cons. Finally, based on evidence of the limitations of the model-based approach and the potentialities of the neural networks, the authors propose a new state observer for BLCF estimation as a promising solution among the supporting tools of the control engineering.

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In order to face with the increasing EU restrictions on CO2 emissions from light-duty vehicles, concepts such as the engines downsizing, stop/start systems as well as more costly full hybrid solutions and Waste Heat Recovery (WHR) technologies have been proposed in the last years by OEMs. WHR technologies include Thermo-Electric Generator (TEG), Organic Rankine Cycle (ORC) and Electric Turbo-Compound (ETC) that have been practically implemented on few heavy-duty applications but have not been proved yet as effective and affordable solutions for passenger cars. The paper deals with the analysis of opportunities and challenges of TEG and ETC technologies for a compact car, powered by a turbocharged SI engine. Specifically, the benefits achievable by TEG and ETC have been investigated by simulation analyses carried out by a dynamic engine-vehicle model, validated against steady-state and transient experimental data. The in-cylinder processes and friction losses of the engine are modeled by a black-box scalable parametric approach while grey-box dynamic models are applied for intake/exhaust manifolds and turbocharger. The TEG model is based on existing and commercial thermoelectric materials, specifically Bi2Te3. The simulations have been carried out considering standard driving cycles (i.e. NEDC, WLTC) and the results evidence that significant improvement of fuel economy and CO 2 reduction can be achieved by suitable management and configuration of the WHR systems, depending on engine speed and load and auxiliaries demand.