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T. W. T. Ivens

Bio: T. W. T. Ivens is an academic researcher. The author has contributed to research in topics: Cruise control. The author has an hindex of 1, co-authored 1 publications receiving 5 citations.

Papers
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01 Jan 2010
TL;DR: In this report, insight is given in the potential of Predictive Cruise Control (PCC) with respect to fuel savings in heavy duty trucks and a mathematical routine called Dynamic Programming is used for the optimization of the speed profile.
Abstract: In vehicle energy management, usually the operating point of the engine is influenced in order to save fuel. This holds for both hybrid as conventional vehicles. However, it is also possible to change the power demand at certain points in time. This can be achieved either by changing vehicle properties (e.g. aerodynamics) or by changing the (desired) vehicle speed. This report deals with the latter case and gives insight in the potential of Predictive Cruise Control (PCC) with respect to fuel savings in heavy duty trucks. PCC uses future road profile information to determine the ideal speed profile, allowing small deviations from the cruise control set speed. A mathematical routine called Dynamic Programming is used for the optimization of the speed profile. The DP algorithm used in this report appeared to be very slow due to complexity of definitions inside it, but simulations have been performed. This is done for a heavy duty DAF truck in several test cases, giving insight in how and when the fuel savings are realized. On and around a small hill, an average fuel saving of 4.76% is realized, which corresponds to findings from literature. The fuel saving results from more efficient use of the engine and avoiding braking.

5 citations


Cited by
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Proceedings ArticleDOI
20 Nov 2014
TL;DR: A novel approach to online velocity trajectory planning for manual energy efficient driving which involves Model Predictive Control for map-based anticipatory driving of heavy duty vehicles is presented and the calculation time of the MPC optimization process with a two kilometer long preview horizon is significantly reduced.
Abstract: This paper presents a novel approach to online velocity trajectory planning for manual energy efficient driving which involves Model Predictive Control (MPC) for map-based anticipatory driving of heavy duty vehicles. The proposed model leads to a Quadratic Programming (QP) optimization problem with sparse matrix structure, allowing to be solved robustly and efficiently. By reducing the optimization problem to a QP standard form, existing and well-proven QP solvers can be used to calculate a reliable solution for a real-time vehicle control application. Evaluations show that the calculation time of the MPC optimization process with a two kilometer long preview horizon is, compared to other literature, significantly reduced to 1.8 milliseconds, while in real-world driving experiments an average fuel consumption reduction of 11.4% compared to normal driving is measured.

22 citations

Proceedings ArticleDOI
08 Jun 2014
TL;DR: This paper presents how to determine the fuel-optimized operating strategies of passenger cars under cruising process by using the Legendre pseudospectral method and the formation of periodic operation are analyzed and explained.
Abstract: Eco-driving technologies are able to largely reduce the fuel consumption of ground vehicles. This paper presents how to determine the fuel-optimized operating strategies of passenger cars under cruising process. The design naturally casts into an optimal control problem with the S-shaped engine fueling rate as the integrand of cost function. The solutions are numerically solved by the Legendre pseudospectral method, of which many are found to demonstrate periodic behaviors. In the periodic operation, the engine switches between the minimum brake specific fuel consumption (BSFC) point and the idling point, while the vehicle speed oscillates between its upper and lower bounds. The formation of periodic operation are analyzed and explained by the π-test theory and steady state analysis method.

17 citations

Proceedings ArticleDOI
27 Aug 2015
TL;DR: A significant improvement of the computation time is demonstrated, while maintaining (or even increasing) the fuel consumption reduction, which is 8.1 percent with the proposed approach compared to a standard cruise controller, without a decrease in the average cruising speed.
Abstract: This paper presents an improved approach to the problem of energy efficient driving of heavy duty vehicles. The proposed model for a map-based Model Predictive Control (MPC) leads to an underlying Quadratic Programming (QP) optimization problem, allowing computationally efficient and robust solutions. A parameter estimation procedure is developed for a vehicle- and optimization-independent parametrization of the tradeoff between saving energy and keeping a desired vehicle velocity. Extensive simulations on a highway scenario for different optimization parameters give further insight to optimization properties, which can be utilized to enhance control performance. Compared to previous literature, we demonstrate a significant improvement of the computation time to under one-fifth of a millisecond, while maintaining (or even increasing) the fuel consumption reduction, which is 8.1 percent with the proposed approach compared to a standard cruise controller, without a decrease in the average cruising speed.

12 citations

DOI
01 Jul 2020
TL;DR: In this article, a Fahrerassistenzsystem is presented, in which a planner is proposed auf Strategie-and Stabilisierungsansatz hergeleitet, der Regelungsaufgabe auf eineStrategie and eine Stabilizierungsebene verteilt.
Abstract: Im Rahmen der vorliegenden Arbeit wird ein Fahrerassistenzsystem fur vorausschauendes automatisiertes Fahren entwickelt. Es umfasst die Langs- und Querfuhrung des Fahrzeugs sowie die Steuerung der relevanten Triebstrangkomponenten. Dabei werden Vorausschauinformationen uber die Fahrzeugumgebung ausgewertet, um ein energie- und komfortoptimales Fahrverhalten zu erreichen. Fur die echtzeitfahige optimale Regelung wird ein Stabilisierungsansatz hergeleitet, der die Regelungsaufgabe auf eine Strategie- und eine Stabilisierungsebene verteilt. Er verbindet die fur eine genaue Strategieplanung notwendige lange Zykluszeit mit einer hochfrequenten, optimalen Storungskompensation. Zur Planung auf Strategie- und Stabilisierungsebene wird ein dreistufiges Verfahren entworfen. Es setzt sich aus einer regelbasierten Einschrankung des Suchraums, einer Initialschatzung mittels Dynamischer Programmierung und einer lokalen Suche nach der Optimaltrajektorie zusammen; die Suche wird zusatzlich durch Heuristiken und bestehendes Vorwissen gesteuert. Es wird eine Methodik hergeleitet, um das System hinsichtlich Regelgute und Berechnungsaufwand optimal auszulegen. Die Einflusse von Stabilisierungsansatz sowie Horizont und Genauigkeit der Trajektorienplanung werden dafur simulativ ausgewertet. Zur Simulation der vorausschauenden Regelung wird ein Ansatz entwickelt, der es ermoglicht, in Versuchsfahrten gemessene Fahrzeug- und Umgebungsdaten mit einem reaktiven Fahrzeugmodell zu kombinieren. Die Funktionsweise des Assistenzsystems im realen Fahrbetrieb wird am Beispiel verschiedener Fahrsituationen exemplarisch diskutiert.

5 citations

20 Mar 2016
TL;DR: In this paper, a look-ahead anticipatory control (LA) method is designed to adjust longitudinal motion (signified by velocity of the vehicle system) using knowledge of fluctuations in road grade.
Abstract: This work answers the need for improvement in fuel Economy in heavy duty vehicles (HDV’s), in a manner simple enough to be used in open road missions. A lookahead anticipatory control (LA) method is designed to adjust longitudinal motion (signified by velocity of the vehicle system) using knowledge of fluctuations in road grade. The prediction of driving behaviour is done using a fuzzy logic function based on a predefined rule-base. Control action of the brake and throttle positions are implemented by taking the state-dependent riccati Equation approach. The results of the proposed controller are compared against those of a standard PI cruise controller. Moreover, results of simulations on a 40 ton vehicle show the proposed method capable of increasing fuel economy.