Nowadays, road vehicles, including trucks, are characterized by an increasedcomplexity due to a greater variety of software, and a greater number of sensorsand actuators. As a consequence, there is an increased risk in termsof software or hardware failures that could lead to unacceptable hazards.Thus safety, more precisely functional safety, is a crucial property that mustbe ensured to avoid or mitigate these potential unacceptable hazards. Inthe automotive domain, recently (November 2011), the ISO-26262 safetystandard has been introduced to provide appropriate requirements and processes.More specically, the standard denes the system development processthat must be carried out to achieve a system that can be consideredacceptably safe. To be released on the market, systems must be certied,proofs that the systems are acceptably safe must be provided in terms of astructured argument, known as safety case, which inter-relates evidence andclaims. Certication authorities are in charge of evaluating the validity ofsuch safety cases. In the automotive domain, certication and compliancewith the standard ISO-26262 is becoming mandatory. By now, trucks donot have to be compliant with the standard. However, it is likely that by2016 they will have to. Scania is one of the leading companies in trucksdevelopment. To be ready by 2016, Scania is interested in investigatingISO-26262 as well as safety case provision. Thus this thesis focuses on theprovision of a safety case in the context of ISO-26262 for Fuel Level Estimationand Display System (FLEDS), which is one of the safety-criticalsystems in Scania.1

Safety-critical systems require high quality and dependability levels, where system correctness and safety are major features to avoid any severe outcome. Time and cost are also important challenges that are imposed during the development process. Describing the behavior of a system in a high level provides a realistic vision and anticipation of the system. This presents a valuable opportunity for verifying the system before wasting the intended resources to develop the system. Architecture Description Languages (ADLs) provide the ability to comprise and represent the system level details of components, interactions and configuration. Architecture Analysis and Design Language (AADL) as a family member of ADLs proved its effectiveness in designing software intensive systems. In this report, we present a case study to validate “An Architecture-Based Verification Technique for AADL Specifications”. The technique involves a combination of model checking and model-based testing approaches adapted to an architectural perspective. The objectives of the verification process are 1) to ensure completeness and consistency of an AADL specification, and 2) to ensure conformance of an implementation with respect to its AADL specification. The technique has only been applied to small examples, and the goal of this thesis work is to validate it against a safety-critical system developed by a major vehicle manufacturer. Validation of the technique begins by investigating the system and specifying it in AADL. The defined verification criteria are subsequently applied to the AADL specification which drives the verification process. The case study presents interesting results while performing the model checking (the completeness and consistency checking). Conformance testing, on the other hand, could not be performed on the implemented system but is an interesting topic for future work.

Knowing how much fuel there is in a car is important for a predictable driving experience. Such knowledge will dictate how a person drives, when to refuel and how long they can drive. However unprocessed fuel level signals are highly noisy and therefore misleading.To ensure a good and predictable driving experience it is important to estimate the fuel level. The way this thesis has tackled this problem is by comparing and evaluating different filtering methods.The estimation algorithms were designed based on a saddle type tank developed by Volvo Car Corporation. The fuel level sensor consists of a floater arm and can only detect fuel levels within its maximal and minimal positions. The tank size can deviate from the standard volume and it will affect the measurement. Acceleration, angular orientation and fuel consumption are all factors that disturb fuel level estimation and therefore their relationship to the estimation problem is investigated. An experiment was devised to investigate the relationship between angular orientation, fuel volume and fuel level readings. ARX based models were made including angular orientation or acceleration. The relationship was concluded to be non-linear. The Kalman, $H_{\infty}$, Particle and Recursive Least Squares filters were compared. The Kalman and RLS filters had the most desirable traits and were therefore further developed. Both Kalman and RLS resulted in smooth estimates on the driving cycles tested.The Kalman filter provided a steadier estimate and could be easily tuned for faster convergence to zero. The Kalman filter can easily be changed to accommodate parametric uncertainties which improve its robust qualities.However the relationship between angular orientation and fuel level readings are non-linear. Therefore the RLS method was considered more robust for a reduced biased fuel reading under angular orientations. In conclusion the most desirable filter is a filter that provides the best traits from both filters.