Simulation and Control of an Automotive Dry Clutch

Abstract-In this paper the dynamic behavior and control of an automotive dry clutch is analyzed. Thereto, a straightforward model of the clutch is embedded within a dynamic model of an automotive powertrain comprising an internal combustion engine, drivetrain and wheels moving a vehicle through tire-road adhesion. The engagement of the clutch is illustrated using the model best suited for simulation, based on work of Karnopp. These simulation results are used for conceiving a decoupling controller for the engine and clutch torque. Simulation results with the controller show significant improvement over the un-controlled case in terms of vehicle launch comfort. A modified controller is proposed that results in even more appreciated drive comfort while not deteriorating other system behavior

Optimal control of a flywheel-based automotive kinetic energy recovery system

This thesis addresses the control issues surrounding flywheel-based Kinetic Energy Recovery Systems (KERS) for use in automotive vehicle applications. Particular emphasis is placed on optimal control of a KERS using a Continuously Variable Transmission (CVT) for volume car production, and a wholly simulation-based approach is adopted. Following consideration of the general control issues surrounding KERS operation, a simplified system model is adopted, and the scope for use of optimal control theory is explored. Both Pontryagin’s Maximum Principle, and Dynamic Programming methods are examined, and the need for numerical implementation established. With Dynamic Programming seen as the most likely route to practical implementation for realistic nonlinear models, the thesis explores several new strategies for numerical implementation of Dynamic Programming, capable of being applied to KERS control of varying degrees of complexity. The best form of numerical implementation identified (in terms of accuracy and efficiency) is then used to establish via simulation, the benefits of optimal KERS control in comparison with a more conventional non-optimal strategy, showing clear benefits of using optimal control

Acausal Powertrain Modelling with Application to Model-based Powertrain Control

The automotive industry has long been searching for efficient ways to improve vehicle performance such as drivability, fuel consumption, and emissions. Researchers in the automotive industry have tried to develop methods to improve fuel consumption and reduce the emission gases of a vehicle, while satisfying drivability and ride comfort issues. Today, by developing computer/software technologies, automotive manufacturers are moving more and more towards modelling a real component (prototype) in a software domain (virtual prototype). For instance, modelling the components of a vehicle's powertrain (driveline) in the software domain helps the designers to iterate the model for different operating conditions and scenarios to obtain better performance without any cost of making a real prototype. The objective of this research is to develop and validate physics-based powertrain models with sufficient fidelity to be useful to the automotive industry for rapid prototyping. Developing a physics-based powertrain model that can accurately simulate real phenomenon in the powertrain components is of great importance. For instance, a high-fidelity simulation of the combustion phenomenon in the internal combustion (IC) engine with detailed physical and chemical reactions can be used as a virtual prototype to estimate physical prototype characteristics in a shorter time than it would take to build a physical prototype. Therefore, the powertrain design can be explored and validated virtually in the software domain to reduce the cost and time of product development. The main focus of this thesis is on development of an internal combustion engine model, four-cylinder spark ignition engine, and a hydrodynamic torque converter model. Then, the models are integrated along with the rest of a powertrain's components (e.g. vehicle longitudinal dynamics model) through acausal connections, which represents a more feasible physics-based powertrain model for model-based control design. The powertrain model can be operated at almost all operating conditions (e.g. wide range of the engine speeds and loads), and is able to capture some transient behaviour of the powertrain as well as the steady state response. Moreover, the parametric formulation of each component in the proposed powertrain model makes the model more efficient to simulate different types of powertrain (e.g. for a passenger car or truck)

Optimalno upravljanje automatskim mjenjačem s velikim brojem stupnjeva prijenosa

Suvremeni automatski mjenjači s planetarnim prijenosnicima uključuju velik broj stupnjeva prijenosa (i do 10), s ciljem smanjenja potrošnje goriva i emisija štetnih plinova, te poboljšanja voznih performansi. U prisustvu složene strukture mjenjača s mnogostrukim kombinacijama i profilima uključivanja spojki, potrebno je postići optimalne karakteristike upravljanja mjenjačem. U radu se prvo prikazuje modeliranje dinamike pogona vozila, s naglaskom na razvoj metoda automatskog modeliranja i automatskog reduciranja reda modela automatskog mjenjača. Automatsko generiranje modela automatskog mjenjača punog reda provodi se izravno iz veznog dijagrama mjenjača, te se taj model koristi za automatsko generiranje modela mjenjača reduciranog reda za proizvoljno, korisnički-definirano stanje spojki. U nastavku rada provodi se numeričko optimiranje upravljačkih varijabli promjene stupnja prijenosa automatskog mjenjača primjenom pseudospektralne kolokacijske metode. Temeljni cilj ove aktivnosti je dobivanje uvida u optimalno ponašanje automatskog mjenjača, posebice kod složenijih promjena stupnja prijenosa s dvostrukim prijelazom, kod kojih se istovremeno koriste četiri spojke. Zatim se predlažu praktični, po odsječcima linearni profili upravljačkih varijabli, koji se definiraju temeljem uvida dobivenih primjenom općeg pristupa optimiranja upravljačkih varijabli. Optimalne vrijednosti parametara loma tako definiranih upravljačkih profila (tj. upravljačkih strategija) određuju se primjenom više-kriterijskog optimiranja, pri čemu se rezultati optimiranja koriste za vrednovanje predloženih upravljačkih strategija uz preporuke za primjenu. S ciljem dobivanja optimalnog rješenja u prisustvu statistički poznatih varijacija temeljnih parametara odziva spojki s aktuatorom, u radu se provodi i stohastičko robusno optimiranje parametara profila upravljačkih varijabli. Konačno, dobiveni rezultati koriste se za sintezu realnog sustava upravljanja u interakciji s komandama vozača i za razne uvjete vožnje. Korištenje razvijenih metoda za modeliranje i optimiranje demonstrira se na primjeru naprednog 10-brzinskog automatskog mjenjača