Développement d'un système d'assistance à la conduite sûr et efficient pour le véhicule électrique

Les progrès dans les domaines des véhicules autonomes, l'hybridation du groupe motopropulseur et les systèmes de transport intelligents (STI) signifient que l'automobile en tant que machine est sur le point d'être réinventée. Les trois domaines technologiques sus-cités ont ouvert des portes sur des avancées possibles au niveau de l'amélioration de la sécurité routière et de l'efficacité énergétique des véhicules qui étaient auparavant limitées en raison de plusieurs facteurs, comme les capacités de détection et de puissance de calcul. Dans ce contexte, un contrôleur de la dynamique longitudinale du véhicule électrique est mis au point et étudié de façon à réaliser un compromis entre sécurité et efficacité du véhicule. Ce système est appelé Smart And Green Adaptive Cruise Control (SAGA).Le développement de cette fonction est basée sur l'optimisation de l'énergie ainsi que sur des stratégies de régénération d'énergie en respectant les contraintes des composants du groupe motopropulseur comme la charge de la batterie, la capacité de freinage du moteur et de la situation courante dans le trafic routier. Dans ce processus, des techniques d'optimisation comme la programmation dynamique et la stratégie de minimisation de la consommation d'énergie équivalente (ECMS) sont utilisés. Utilisant des modèles d'énergie du véhicule et des modèles cinématiques intégrés sur Matlab-Simulink, ce travail de thèse évalue les avantages et les limites de l'utilisation de la fonction SAGA pour diverses topologies de véhicules pour différents scénarios de trafic.The progress in the fields of autonomously driven vehicles, powertrain hybridization and Intelligent transportation systems (ITS) means that the automobile as a machine, is on the verge of reinvention. The aforementioned three fields of technologies have opened doors to advanced opportunities in improvement of safety and efficiency of vehicles which were earlier limited due to several factors like sensing capacities and computational power.In this context, a vehicle longitudinal motion controller is developed and investigated which will actively balance vehicle safety and efficiency. It is named as the Smart and Green Adaptive Cruise Control System (SAGA). Development of this function is based on optimization of energy supply as well as energy regeneration strategies with respect to powertrain component constraints like battery charge acceptance, motor braking capacity and traffic situation. In this process, optimization techniques like Dynamic programming and Equivalent Consumption Minimization Strategy (ECMS)are used. Using vehicle energy and kinematic models built in Matlab-Simulink platform, this dissertation evaluates the advantages and limitations of using SAGA function for various vehicles topologies and in different traffic scenarios

Smart and Green ACC series: A city and highway specific approach towards a safe and efficient eDAS

The successful transition of fully electric vehicle into automotive market is plagued with expensive product prices and limited drive range. While manufacturers point to fuel saving benefits, the actual cost savings after the first battery replacement presents negative economics. Hence it is necessary to maximise the fuel saving costs and to prolong the battery life as much as possible. The situation calls for an assistant system which takes into consideration the inherent propulsion system dynamics of electric vehicle in two typical situations – namely city and highway. Here we propose a combination of two systems, first a dynamic programming based acceleration controller for city cycle and second, an eHorizon based ACC system for maximum recuperation on highways. This paper is an extension of papers [1,2] and forms a series which is attributed to the development of a partial or complete “Safe and energy efficient longitudinal vehicle controller”. Such a controller is named “SAGA” - Smart and Green Automated Cruise Control. It is an ecological driver assistance system (eDAS) that adapts the vehicle speed over all its speed range according to a forward vehicle and to road events in a near horizon (legal speed, curves, etc…) with an aim to reduce the energy consumption without compromising on safety

Smart and Green ACC: Energy and Safety Optimization Strategies for EVs

International audienceMinimum energy expense and maximum safety with some comfort characterizes the definition of ideal human mobility. Recent technological advances in the autonomous vehicle driving systems not only enhance the safety and/or comfort levels but also present a significant opportunity for automated eco-driving. In this regard, a longitudinal controller for a smart and green autonomous vehicle (SAGA) is investigated. In principle, it is an eco-adaptive cruise control which aims at minimizing energy expenditure and maximizing energy regeneration. This paper presents detailed energy and powertrain analysis through the simulation of specific SAGA application concepts such as, dynamic programming-based offline acceleration optimization for a battery electric vehicle, or SAGA as a supervisory controller in combination with equivalent consumption minimization strategy for a hybrid electric vehicle. The main focus is on the evaluation of a vehicle energy manager which autonomously controls the longitudinal motion while actively balancing efficiency and safety. The comfort is not directly addressed in the conception but regarded as a quality criterion

Smart and green ACC: Energy and safety optimization strategies for EVs

Minimum energy expense and maximum safety with some comfort characterizes the definition of ideal human mobility. Recent technological advances in the autonomous vehicle driving systems not only enhance the safety and/or comfort levels but also present a significant opportunity for automated eco-driving. In this regard, a longitudinal controller for a smart and green autonomous vehicle (SAGA) is investigated. In principle, it is an eco-adaptive cruise control which aims at minimizing energy expenditure and maximizing energy regeneration. This paper presents detailed energy and powertrain analysis through the simulation of specific SAGA application concepts such as, dynamic programming-based offline acceleration optimization for a battery electric vehicle, or SAGA as a supervisory controller in combination with equivalent consumption minimization strategy for a hybrid electric vehicle. The main focus is on the evaluation of a vehicle energy manager which autonomously controls the longitudinal motion while actively balancing efficiency and safety. The comfort is not directly addressed in the conception but regarded as a quality criterion

Smart and green ACC: As applied to a through the road hybrid electric vehicle

The Smart and Green ACC (SAGA) or simply Green ACC (GACC) may be defined as a system which autonomously generates longitudinal control commands for a vehicle while balancing the safety and efficiency factors. In previous studies, the SAGA function is investigated as applied to a battery electric vehicle. As a continuation of the SAGA function development, this paper investigates the behavior of the autonomous longitudinal controller as applied to a “Through the Road” (TtR) hybrid electric vehicle. Given the presence of two power sources, the implementation of a SAGA system in HEV/PHEV has a higher level of complexity as compared to pure EV. As an autonomous longitudinal driver command generating system, SAGA acts as a surficial controller which is then combined with a core powertrain management system. The Equivalent Consumption Minimization Strategy (ECMS) is used to determine the optimum power split between the IC engine and electric motor

Smart and Green ACC series: A city and highway specific approach towards a safe and efficient eDAS

The successful transition of fully electric vehicle into automotive market is plagued with expensive product prices and limited drive range. While manufacturers point to fuel saving benefits, the actual cost savings after the first battery replacement presents negative economics. Hence it is necessary to maximise the fuel saving costs and to prolong the battery life as much as possible. The situation calls for an assistant system which takes into consideration the inherent propulsion system dynamics of electric vehicle in two typical situations - namely city and highway. Here we propose a combination of two systems, first a dynamic programming based acceleration controller for city cycle and second, an eHorizon based ACC system for maximum recuperation on highways. This paper is an extension of papers [1,2] and forms a series which is attributed to the development of a partial or complete “Safe and energy efficient longitudinal vehicle controller”. Such a controller is named “SAGA” - Smart and Green Automated Cruise Control. It is an ecological driver assistance system (eDAS) that adapts the vehicle speed over all its speed range according to a forward vehicle and to road events in a near horizon (legal speed, curves, etc...) with an aim to reduce the energy consumption without compromising on safety

Smart and Green Autonomous Vehicle Controller: Enhancement of Regeneration and Powertrain Strategy

International audienc

Smart and Green ACC, Safety and Efficiency for a Longitudinal Driving Assistance

International audienceDriving Assistances aim at enhancing the driver safety and the comfort. Nowadays, the consumption is also a major criterion which must be integrated in the driving assistances. Then, we propose to redefine the behavior of an ACC with energy efficiency consideration to perform a Smart and Green ACC. We apply our development to the specific use case of the electric vehicle that allows regenerative braking. The ACC, once activated, operates under two possible modes (speed control and headway spacing control). We define the behavior of the driving assistance under these both possible modes, focusing on the distance control. We present the efficiency of various strategies without trading off safety. We conclude on the efficiency by presenting several use cases that show the SAGA behavior

Electric Vehicle Modeling for energy optimization : an eFuture project result

International audienc

Smart and Green ACC, adaptation of the ACC strategy for electric vehicle with regenerative capacity

This paper presents an optimization of a conventional Adaptive Cruise Control system (ACC) for the specific use of electric vehicles with regenerative capacity, namely the Smart and Green ACC (SAGA). Longitudinal control strategies, that are developed for the driving assistances, mainly aim at optimizing the safety and the comfort of the vehicle occupants. Electric vehicles have the possibility, depending on the architecture, the speed and the braking demand, to regenerate a part of the electric energy during the braking. Moreover, the electric vehicle range is currently limited. The opportunity to adapt the braking of an ACC system to extend slightly the range must not be avoided. When the ACC is active, the vehicle speed is controlled automatically either to maintain a given clearance to a forward vehicle, or to maintain the driver desired speed, whichever is lower. We define how we can optimize both mode and what is the impact, in term of safety and strategy, including the knowledge of the future of the road, integrating a navigation system