Abdelkrim Doufene

Planning an itinerary for an electric vehicle

The steady increase in oil prices and awareness regarding environmental risks due to carbon dioxide emissions are promoting the current interest in electric vehicles. However, the current relatively low driving range (autonomy) of these vehicles, especially compared with the autonomy of existing internal combustion vehicles, remains an obstacle to their development. In order to reassure a driver of an electric vehicle and allow him to reach his destinations beyond the battery capacity, we describe a system which generates an energy plan for the driver. We present in this paper the electric vehicle ecosystem and we focus on the contribution of using the generalized multi-commodity network flow (GMCNF) model as a vehicle routing model that considers energy consumption and charging time in order to ensure the usage of an electric vehicle beyond its embedded autonomy by selecting the best routes to reach the destination with minimal time and/or cost. We also present some perspectives related to the utilization of autonomous electric vehicles and wireless charging systems. We conclude with some open research questions.

Complex Systems Architecture Framework: Extension to Multi-objective Optimization

This paper shows the utility to follow an architecture framework in order to design complex systems with a holistic approach. Multi-objective Optimization techniques extend and complete the architecture framework to support trade-off analysis and decision making in the Systems Engineering design process. The merging and combination of these two approaches, decision making and systems engineering, contribute to the efficient design of systems by helping to meet needs and constraints stemming mainly from the system analysis.

Pareto optimality and Nash equilibrium for building stable systems

This paper introduces a design approach based on system analysis and game theory for the identification of architectural equilibrium which guarantees the stability of the system being designed and its environment after the integration. We introduce multi-objective optimization and game theory, and their links with systems engineering through mathematical models. While Pareto optimality is used to select best architectures and to support independent decisions, Nash equilibrium is used to find out architectural equilibrium and to support interdependent decisions. This approach was illustrated previously in a case study.

Assessment of Resilience in Desalination Infrastructure Using Semi-Markov Models

As the supply of desalinated water becomes significant in many countries, the reliable long-term operation of desalination infrastructure becomes paramount. As it is not realistic to build desalination systems with components that never fail, instead the system should be designed with more resilience. To answer the question how resilient the system should be, we present in this paper a quantitative approach to measure system resilience using semi-Markov models. This approach allows to probabilistically represent the resilience of a desalination system, considering the functional or failed states of its components, as well as the probability of failure and repair rates. As the desalination plants are connected with the end-user through water transportation and distribution networks, this approach also enables an evaluation of various network configurations and resilience strategies. A case study addressing a segment of the water system in Saudi Arabia is given with the results, benefits, and limitations of the technique discussed.

System architecture and optimization to support variability and flexibility in design

The coupling of the desalination process with solar technology is a complex problem. As various types of desalination processes and solar technologies have been developed, the selection of the best combination requires several design criteria. Capital costs, operation and maintenance costs, plant site, salinity of seawater, environmental impacts, and water quantity and quality requirements are examples of the design criteria involved in selecting a suitable desalination process. On the other hand, the selection of a suitable solar system is governed by a number of factors such as plant configuration, energy storage, location, working fluids, etc. Moreover, when integrating the solar technology and desalination processes, more requirements and constraints arise. A generic design would reduce the cost of engineering studies and the time to market thanks to the reuse of existing designs, and the ability to adapt a technical solution according to a given context (the best architectures according to a context (both spatial and temporal)). We use a design framework, completed by multi-objective, multidisciplinary optimization models in order to manage variability (space - different locations then different natural environment characteristics mainly sea water quality, solar radiation and dust) and flexibility (time-increase of demand overtime).