The development of new automotive functions in a car must comply with the AUTOSAR standard. Such functions are distributed over the ECUs of the car connected with buses. The development of these distributed functions is not easy in AUTOSAR because there is no global view of the system. In this paper we propose an approach that counters this difficulty by designing automotive systems with a global view and then transforming these systems into AUTOSAR systems.
Electric vehicles embed a low amount of energy, so their devices need to be managed efficiently to optimize the vehicle autonomy. A vehicle management is achieved by the embedded systems, modeled following the Autosar standard. Autosar covers most of the automotive concerns, but it lacks energy consumption and user-oriented Quality of Service models. This paper presents Orqa, a framework to model and manage the electric vehicle devices through energy consumption and user-oriented Quality of Service. At design time, the architects choose and tune the actual vehicle device models through their power requirements and, if appropriate, quality levels. The generated implementation is then embedded in the existing Autosar models. Thus, at run-time, the vehicle's system is able to evaluate the global consumption of a trip and to propose the user a specific driving strategy. The optional devices are managed throughout the trip, based on the driver preferences. Orqa is illustrated with a classic use-case: a work to home trip.
Abstract-Energy management of electric vehicles has been the focus of recent research to allow optimal engine and battery usage. Many efforts have been realised to use the trip knowledge -or a prediction of it -to provide the best vehicle efficiency. Yet few works take into account the embedded devices and the vehicle global Quality of Service. The ORQA framework has a vehicle systemic approach, its purpose is to generate an architecture to counter the range anxiety and offer the best quality effort based on the driver preferences. The work described in this paper is about the off-line configuration of the ORQA framework to match a target vehicle characteristics and abilities. With a more precise configuration, the on-line execution of ORQA is optimised. Two leads are presented to reduce the computation time needed to explore the solution space on-line. The final result is an energy management software tuned for a specific targeted vehicle which offers a driving strategy and a control of the embedded devices matching the driver destination and preferences.
The energy management of electric vehicles is located in the storage system. It considers only the storage physical constituents and adapts the demand of the drive-chain technologies but is blind to other parts of the vehicle. Furthermore it has a very focused approach -to optimise the vehicle movement -and misses the driver's pragmatical needs. ORQA is a framework dedicated to the modelling of the vehicle consuming devices complementing the embedded systems models. It characterises each consuming device by its energetic needs and the quality levels it offers from a driver perspective. ORQA is realised by a system-level energy manager which looks for a driving strategy matching the driver needs and constraints. As the components used in ORQA are generic devices, the consumption of the devices is an approximation of their real consumptions. This paper presents the adaptation of the ORQA framework to have a closer estimation of the consuming devices. We propose the use of physical models issued from mechatronic systems for the main devices, drive-chain and energy storage, and discuss the benefits and constraints.
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