Peter Lindroth

Regulation of glutamate biosynthesis and release in vitro by low levels of ammonium ions

The content and release of endogenous amino acids from isolated rat hippocampal slices were measured. The tissue was perfused with control media and pulsed with high potassium media in order to induce synaptic release. Pathophysiological concentrations of ammonium ions (3--5 mM) were added to the control medium for 60 min prior to the induced release. Amino acids belonging to the putative transmitter group were released extensively during potassium perfusion and, except for glutamate, even after ammonium ion perfusion. The spontaneous secretion of glutamate increased, however, slowly after the addition of ammonia. The incorporation of 14C from radiolabelled glucose and acetate into the amino acid fraction was studied in the presence of ammonia-containing media. Glucose was utilized to a moderately increasing extent, but acetate-derived radioactivity was strikingly decreased in the amino acid fraction during ammonia perfusion. The decreased acetate incorporation into amino acids was mainly due to an inhibition by ammonia of the accumulation of acetate by the CNS tissue.

Approximating the Pareto optimal set using a reduced set of objective functions

Real-world applications of multi-objective optimization often involve numerous objective functions. But while such problems are in general computationally intractable, it is seldom necessary to determine the Pareto optimal set exactly. A significantly smaller computational burden thus motivates the loss of precision if the size of the loss can be estimated. We describe a method for finding an optimal reduction of the set of objectives yielding a smaller problem whose Pareto optimal set w.r.t. a discrete subset of the decision space is as close as possible to that of the original set of objectives. Utilizing a new characterization of Pareto optimality and presuming a finite decision space, we derive a program whose solution represents an optimal reduction. We also propose an approximate, computationally less demanding formulation which utilizes correlations between the objectives and separates into two parts. Numerical results from an industrial instance concerning the configuration of heavy-duty trucks are also reported, demonstrating the usefulness of the method developed. The results show that multi-objective optimization problems can be significantly simplified with an induced error which can be measured.

Modelling of optimal tyres selection for a certain truck and transport application

The main aim of the research leading to this paper is to select---for a truck and its transport application---a configuration of the tyres such that the energy losses caused by these are minimized. We show that neither the rolling resistance coefficient (RRC) classes provided by tyre suppliers nor any other nominal values of RRC evaluated for specific operating conditions are sufficient to do the tyres selection. Therefore, a surrogate model of the RRC is developed. A tyre model based on the RRC model is introduced in this paper. The modularity of the tyre model is demonstrated by coupling it with two different vehicle models and an~operating environment model. The usage of the joint vehicle, tyres, and operating environment model is demonstrated by solving a few illustrative instances of the tyres selection problem. The potential savings wrt. energy losses when the selected tyre configurations are used are presented.

Traffic aware electric vehicle routing

Since the main constraint of electric vehicles is range due to limited battery capacity, the focus for routing these kind of vehicles should be energy consumption minimization. And since energy consumption depends on several aspects, this article introduces a new model for route optimization of Electric Commercial Vehicles, with a realistic energy consumption model based on factors such as road inclination, weight and speed. The main new feature is to consider average speed for the road network at different times during the day, with the vehicle driving at the highest speed allowed by the traffic flow in order to also minimize total time. Several experiments were performed to evaluate the impact of different elements in energy consumption and routing. As a result a few topics are recommended for future work.

Rule-based optimization and multicriteria decision support for packaging a truck chassis

ABSTRACT Trucks are highly individualized products where exchangeable parts are flexibly combined to suit different customer requirements, this leading to a great complexity in product development. Therefore, an optimization approach based on constraint programming is proposed for automatically packaging parts of a truck chassis by following packaging rules expressed as constraints. A multicriteria decision support system is developed where a database of truck layouts is computed, among which interactive navigation then can be performed. The work has been performed in cooperation with Volvo Group Trucks Technology (GTT), from which specific rules have been used. Several scenarios are described where the methods developed can be successfully applied and lead to less time-consuming manual work, fewer mistakes, and greater flexibility in configuring trucks. A numerical evaluation is also presented showing the efficiency and practical relevance of the methods, which are implemented in a software tool.

Design and development of a road profile generator

This work aims to develop a method of generating a random road profile in three-dimensional space based on existing road design and classification standards and parameters, such examples being the Volvo Global Transport Application (GTA) and the International Organization of Standards (ISO). This is done by combining probability models, statistical distributions and mathematical methods of defining road curves, elevation and surface roughness through the use of MATLAB code. The proposed road profile generator code creates a road in three-dimensional space independent of vehicle characteristics and behaviour. The ultimate goal of this work is to contribute to the capabilities of modern virtual vehicle simulation systems by incorporating more random environments with respect to a wide range of established national standards to better simulate real driving loads.

Modeling and solving vehicle routing problems with many available vehicle types

Vehicle routing problems (VRPs) involving the selection of vehicles from a large set of vehicle types are hitherto not well studied in the literature. Such problems arise at Volvo Group Trucks Technology, that faces an immense set of possible vehicle configurations, of which an optimal set needs to be chosen for each specific combination of transport missions. Another property of real-world VRPs that is often neglected in the literature is that the fuel resources required to drive a vehicle along a route is highly dependent on the actual load of the vehicle.