Ross McMurran

Probability based vehicle fault diagnosis: Bayesian network method

Fault diagnostics are increasingly important for ensuring vehicle safety and reliability. One of the issues in vehicle fault diagnosis is the difficulty of successful interpretation of failure symptoms to correctly diagnose the real root cause. This paper presents an innovative Bayesian Network based method for guiding off-line vehicle fault diagnosis. By using a vehicle infotainment system as a case study, a number of Bayesian diagnostic models have been established for fault cases with single and multiple symptoms. Particular considerations are given to the design of the Bayesian model structure, determination of prior probabilities of root causes, and diagnostic procedure. In order to unburden the computation, an object oriented model structure has been adopted to prevent the model from overly large. It is shown that the proposed method is capable of guiding vehicle diagnostics in a probabilistic manner. Furthermore, the method features a multiple-symptoms-orientated troubleshooting strategy, and is capable of diagnosing multiple symptoms optimally and simultaneously.

Regenerative braking strategies, vehicle safety and stability control systems: critical use-case proposals

The sustainable development of vehicle propulsion systems that have mainly focused on reduction of fuel consumption (i.e. CO2 emission) has led, not only to the development of systems connected with combustion processes but also to legislation and testing procedures. In recent years, the low carbon policy has made hybrid vehicles and fully electric vehicles (H/EVs) popular. The main virtue of these propulsion systems is their ability to restore some of the expended energy from kinetic movement, e.g. the braking process. Consequently new research and testing methods for H/EVs are currently being developed. This especially concerns the critical ‘use-cases’ for functionality tests within dynamic events for both virtual simulations, as well as real-time road tests. The use-case for conventional vehicles for numerical simulations and road tests are well established. However, the wide variety of tests and their great number (close to a thousand) creates a need for selection, in the first place, and the creation of critical use-cases suitable for testing H/EVs in both virtual and real-world environments. It is known that a marginal improvement in the regenerative braking ratio can significantly improve the vehicle range and, therefore, the economic cost of its operation. In modern vehicles, vehicle dynamics control systems play the principal role in safety, comfort and economic operation. Unfortunately, however, the existing standard road test scenarios are insufficient for H/EVs. Sector knowledge suggests that there are currently no agreed tests scenarios to fully investigate the effects of brake blending between conventional and regenerative braking as well as the regenerative braking interaction with active driving safety systems (ADSS). The paper presents seven manoeuvres, which are considered to be suitable and highly informative for the development and examination of H/EVs with regenerative braking capability. The critical manoeuvres presented are considered to be appropriate for examination of the regenerative braking mode according to ADSS. The manoeuvres are also important for investigation of regenerative braking system properties/functionalities that are specified by the legal requirements concerning H/EVs braking systems. The last part of this paper shows simulation results for one of the proposed manoeuvres that explicitly shows the usefulness of the manoeuvre.

Adaptive OSEK Network Management for in-vehicle network fault detection

Rapid growth in the deployment of networked electronic control units (ECUs) and enhanced software features within automotive vehicles has occurred over the past two decades. This inevitably results in difficulties and complexity in in-vehicle network fault diagnostics. To overcome these problems, a framework for on-board in-vehicle network diagnostics has been proposed and its concept has previously been demonstrated through experiments. This paper presents a further implementation of network fault detection within the framework. Adaptive OSEK Network Management, a new technique for detecting network level faults, is presented. It is demonstrated in this paper that this technique provides more accurate fault detection and the capability to cover more fault scenarios.

Automotive Network Diagnostic Systems

Rapid growth in automotive networked embedded systems has occurred over the past two decades. This leads to complexity, especially in fault diagnosis and testing of such systems. This paper reports a work-in-progress automotive network diagnostic system. The aim is to design a system to monitor and diagnose automotive networks, by using a knowledge-based diagnostic technique. Fault information from several sources is used to build a knowledge base. Network fault codes and possible causes diagnosed by a diagnostic module are then stored in a database. The codes are helpful for manufacturing and service processes. This new diagnostic system would contribute to general automotive diagnosis efficiency as it would help reduce numbers of possible fault causes, thereby, correctly pinpointing faulty devices and shortening diagnostic time.

Design validation testing of vehicle instrument cluster using machine vision and hardware-in-the-loop

This paper presents an advanced testing system, combining hardware-in-the-loop (HIL) and machine vision technologies, for automated design validation testing of a vehicle instrument cluster. In the system, a HIL set-up supported by model-based approaches simulates vehicle network in real-time, and provides all essential signals to the instrument cluster under test. The machine vision system with novel image processing algorithms is designed to perform function tests by detecting gauges, warning lights/tell-tales, patterns and text displays. The system developed greatly eases the task of tedious validation testing, and makes onerous repeated tests possible.

Model-based testing of a vehicle instrument cluster for design validation using machine vision

This paper presents an advanced testing system, combining model-based testing and machine vision technologies, for automated design validation of a vehicle instrument cluster. In the system, a hardware-in-the-loop (HIL) tester, supported by model-based approaches, simulates vehicle operations in real time and dynamically provides all essential signals to the instrument cluster under test. A machine vision system with advanced image processing algorithms is designed to inspect the visual displays. Experiments demonstrate that the system developed is accurate for measuring the pointer position, bar graph position, pointer angular velocity and indicator flash rate, and is highly robust for validating various functionalities including warning lights status, symbol and text displays. Moreover, the system developed greatly eases the task of tedious validation testing and makes onerous repeated tests possible.

A Critical Analysis of Model-Based Formal Verification Efforts within the Automotive Industry

There are a number of software-controlled features in todays automotive vehicles to meet the increasing number of requirements for comfort, safety, infotainment and reduced emissions. To meet the growing demands from such features, the software content is not only increasing rapidly, but also becoming increasingly distributed within the Electronic Control Units (ECUs), leading to the possibility of unwanted interactions and consequent loss of reliability. Therefore, the automotive software-based features have to be designed and verified using sophisticated tools and techniques.Formal methods-based techniques and tools have been used on various industrial designs over the past 6 years by one of the authors in development and applied research projects, collaborating with a number of automotive companies. The challenges faced in large projects are discussed in this context. A large number of industrial users have recounted their own experiences in user conferences and workshops, which will be summarized. The results of a short survey of real users will also be discussed in this context.

Model based validation techniques for complex control systems

The complexity of developing todays hybrid powertrain control systems is increasingly being dealt with by the use of model based design methods. This introduces new opportunities, and challenges, in identifying and using advanced validation techniques to best utilise model based design artifacts. This paper discusses some of the advanced validation techniques used within the premium automotive research and development (PARD) programme and identifies further on-going work within a new project called evolutionary validation of complex systems (EvoCS).

Robustness Testing against Low Voltage Transients - A Novel Approach

The increasing use of distributed functions in vehicles can introduce unexpected and undesirable emergent behavior. This can be as a result of transient events such as sudden drops in the supply voltage. In this situation system behavior is often not adequately specified or controlled. This paper presents a novel approach to automotive electronic systems testing addressing robustness against low voltage transient conditions. The paper will discuss the technical output as well as performance in real-world test usage. The proposed approach uses a combination of pseudo-random number generator algorithms to generate parameterized supply voltage waveforms simulating low voltage transient conditions, used to drive the system-under-test (SUT). Two measures are used to judge whether the SUT has passed or failed the test; the detection of unintended recorded Diagnostic Trouble Codes (DTCs) from the error memory of each Electronic Control Unit (ECU) and the detection of unexpected system functionality by a human observer or automated vision system.

Systems modelling of a driver information system - automotive industry case study

This paper describes work done at the IARC, in collaboration with an automotive original equipment manufacturer (OEM) and suppliers, in the project systems modelling language (SysML) for automotive software development and integration. The OEM is interested in how a SysML model could supplement or even replace paper specifications whereas the suppliers are more interested in finding how the resulting SysML model could be used for software development. The project focuses on practical aspects so that deployment of the language and related technology is possible smoothly. The case study involves a driver information system for a premium vehicle. Our industry partner supplied the requirements and specification documents. The progress to-date including the challenges faced, results so far and the plan for further work are detailed