Search Results

The network is becoming the development focus for the in-vehicle electronic system. Network buses are used to improve communication between ECUs and to reduce the wiring costs. In-vehicle network buses, such as CAN, LIN, FlexRay, have become the central technique for sharing sensor data among vehicle ECUs. Gateways are a critical factor in vehicle network design with applications requiring the use of several networking standards. There are lots of networking protocols to choose from - each with advantages and disadvantages. No one protocol satisfies the requirements of all automotive applications. There is a need to consolidate data from these networks using de-centralized processing. As such, a gateway is used as a central hub to interconnect and process data from a vehicle's embedded networks. A gateway is composed of several automotive networking interfaces such as CAN, LIN and FlexRay in addition to embedded micro-controllers and peripheral functions.

This paper proposes a solution to the challenge of developing vehicle software application functions which are decoupled from their intended target hardware platforms. Once developed, these software application functions can be utilised across any OEM vehicle platform and vehicle variants, saving the supplier time and money in terms of system development and giving a number of OEMs similar tried-and-tested system application software. The proposed solution is to use the Model Driven Architecture (MDA)1, a UML-based development approach that separates the specification of system functionality from the specification of the implementation of that functionality on a specific technology platform. MDA allows a vehicle function to be modelled in a semantically rich UML [1,2] model which is completely independent of any implementation detail.

ODX (Open Diagnostics data eXchange) is a standard diagnostic data format specified by the European ASAM group, to simplify the exchange of vehicle diagnostic data between manufacturers, suppliers and service dealerships. The ODX database contains diagnostic data for the whole vehicle together with details of all vehicle ECUs. This paper gives an overview of the main categories of data contained in the ODX diagnostic database. A Windows-based diagnostic application was developed to execute ISO 15765 diagnostic services on ECUs, using an ODX database to define the allowed services and parameters for each ECU. The paper describes the structure of the diagnostic application and the steps that were necessary to process the ODX and tailor it to a production ECU.

The development of vehicle control systems has evolved to become an exercise in the design and integration of complex, distributed hardware and software components. The various components are typically developed by geographically dispersed, multicultural teams from both OEMs and suppliers. This paper gives a brief overview of using the Unified Modelling Language (UML) as a means of capturing the requirements of real-time distributed systems in a graphical notation shared by all team members. UML is commonly used to model system concepts, albeit typically as system “sketches” without any formal definition of the model's semantics. This paper specifically addresses the additions to the latest version of UML that supports higher levels of abstraction, model-based development, executable models and the specification of non-functional requirements.

This paper investigates the process of building a fuzzy logic Electrical Power Steering (EPS) system. The EPS prototype described in the paper dynamically generates a variable torque assist depending on the combination of the momentary values of vehicle weight, velocity, lateral acceleration, battery voltage, and tyre pressure. The process of modeling and simulating the prototype in MATLAB/Simulink is described. The paper presents the research experience indicating that the use of fuzzy logic to design an Electrical Power Steering system delivers a rapid development time and a direct and natural way to capture the required functionality.

This paper looks into the use of simulation software to develop and maintain diagnostic systems on Car networks. It is done through automatic code generation, while also taking advantage of the Real-time benefits of Simulation software. It will concentrate on the Key Word Protocol (KWP 2000) functioning along a CAN-BUS network as a means to illustrate the benefits of the design of such software. The paper will show the development of such software in its separate areas. Each area complies with the relevant ISO standards of Communication at the various ISO layers. It will also show how this is integrated with the external changeable data, using the SIMULINK Simulation software. This will be linked with Microsoft's Excel spreadsheet, allowing the separation of data from the application. Diagnostic code is then automatically generated. This code can be added automatically to an ECU to give it diagnostic functionality. This diagnostic design is easy to use and adaptable to existing models.

As automotive technology becomes more sophisticated the ability to troubleshoot and identify a malfunction becomes a more difficult and complex task, particularly without the assistance of specialised tools. A car manufacturer with the facility to identify and diagnose a malfunction before direct contact from the customer and possibly before the customer becomes aware that a problem exists would have a real competitive advantage in the market place. This paper proposes an architecture that may make this a reality. The architecture enables diagnostic information to be sent to a Case Based Reasoning (CBR) tool at the manufacturers premises when the car enters a hotspot (WI-FI enabled location). The CBR tool subsequently reviews diagnostic information to determine if a malfunction has occurred. If a malfunction is identified the customer is informed of the problem and is prompted to bring the car to a garage.

A modern automobile is becoming far more complex with the release of each new model. Complexity arises in the form of new mechanical devices, electronic devices and nowadays software components. With this increase in complexity, the job of diagnosing a fault is becoming increasingly difficult, as the service technician now requires detailed knowledge in a range of disciplines. This paper describes an Intelligent Diagnostic System (IDS) that was developed to intelligently diagnose faults in a multi-ECU (Electronic Control Unit) environment. Intelligence is achieved by diagnosing several faults while always attempting to isolate a “core” faulty component instead of simply returning a series of faults.

The Centre for Automotive Research WIT is developing a methodology and tool for optimally distributing OSEK Tasks throughout In-Vehicle Networks. This distribution methodology automates the OSEK Task - ECU allocation process, generating optimal solutions for the network, maximizing the number of OSEK Tasks per ECU and therefore allowing for either more complex functionality for the same ECU network or a reduction in the number of ECUs on the network. Overall, this should reduce development time and help save vehicle weight and costs.

It is estimated that the software which monitors the health of an ECU now takes up about 60% of the total ECU software code to monitor, diagnose and announce the problems an ECU may have during its normal or abnormal operational modes. It is the abnormal operation of the system which is the constant problem for vehicle OEMs because this side of the system operation is not easily defined or simulated. The integration of Failure Mode and Effects Analysis (FMEA) to normal design is now becoming central to tackling these issues head-on, such that FMEA is now used as part of the integration process. Having between 10 and 20 different ECUs on a vehicle network still leaves the integration of software from many different suppliers a difficult task.

This paper has two main objectives, firstly to provide a brief understanding of the currently available time-triggered networks that exist in industry today. This is achieved in section one of this paper by introducing a description of each of the main network types. The second objective is to investigate the timing models of a time-triggered network. This is done by producing a static model of the timing considerations of a network, which will then be simulated. The timing model and simulations are dealt with in section two.