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Complex systems, such as modern advanced driver assistance systems (ADAS), consist of many interacting components. The number of options promises considerable flexibility for configuring systems with many cost-performance-value tradeoffs; however the potential unique configurations are exponentially many prohibiting a build-test-fix approach. Instead, engineering analysis tools for rapid design-space navigation and analysis can be applied to find feasible options and evaluate their potential for correct system behavior and performance subject to functional requirements. The OpenMETA toolchain is a component-based, design space creation and analysis tool for rapidly defining and analyzing systems with large variability and cross-domain requirements. The tool supports the creation of compositional, multi-domain components, based on a user-defined ontology, which captures the behavior and structure of components and the allowable interfaces.

Powertrain software development for series production faces multifaceted challenges related to high functional complexity, high quality standards, reduced time to market and high development costs. Software architecture tackles the above mentioned challenges by breaking down the complexity of application software into modular components. Hence, design errors introduced during that phase cause significant cost and time deviations. Early and repeated analysis of new and modified architecture artifacts is required to detect design errors and the impact of the subsequent changes in the software architecture. Engine management software has a high degree of functional complexity and large number of system variants depending upon market requirements. This paper deals with the methods to perform automated evaluation of Renault’s EMS 2012 Engine Management Software in a Continuous Integration Framework.

Virtual testing of advanced driver assistance systems (ADAS) using a simulation environment provides great potential in reducing real world testing and therefore currently much effort is spent on the development of such tools. This work proposes a simulation and hardware-in-the-loop (HIL) framework, which helps to create a virtual test environment for ADAS based on real world test drive. The idea is to reproduce environmental conditions obtained on a test drive within a simulation environment. For this purpose, a production standard BMW 320d is equipped with a radar sensor to capture surrounding traffic objects and used as vehicle for test drives. Post processing of recorded GPS raw data from the navigation system using an open source map service and the radar data allows an exact reproduction of the driven road including other traffic participants.

Huge Simulink controller models often consists of (almost) identical subsystems, very often resulting from copy-and-paste operations and only slight adaptation of the subsystems by the model engineer. Although this “copy-and-paste” approach might help to achieve initial results very fast, in the long-run such subsystem clones can create considerable problems. Like code clones, model clones increase the effort for testing and maintenance. Model clones also tend to influence the code efficiency and code quality in a negative way in case the Simulink model is used as a basis for code generation. JUST SIMPLIFY is an approach for detecting model clones in a Simulink model automatically based on model metrics calculations. This approach has been implemented in our model metrics and complexity measurement tool M-XRAY. JUST SIMPLIFY allows reducing the effort for model refactoring by avoiding time consuming manual search for model clones.

The introduction of ISO 26262 concepts has brought important changes in the software development process for automotive software. While making the process more robust by introducing various additional methods of verification and validation, there has been a substantial increase in the development time. Thus, test automation and front loading approaches have become important to meet product timelines and quality. This paper proposes automated testing methods using formal analysis tools like Simulink Design Verifier™ (SLDV) for boundary value testing and interface testing to address the demands of ISO 26262 concepts at unit and component level. In addition, the method of automated boundary value testing proposed differs from the traditional methods and the authors offer an argument as to why the traditional boundary value testing is not required at unit (function) level. There are two aspects of the proposed method: automated test case generation and automated test case execution.

PEPS (Passive Entry and Passive Start) system is gradually becoming a main stream option in automotive keyless entry application, which improves the convenience and vehicle anti-theft performance. Based on the complex functions and safety technical requirements of the PEPS controller, and due to the development method of the model-based system design widely used in the automotive electronics industry, this paper presents a model-based on the development of PEPS controller method, which introduces the process of modeling and automatic code generation for the PEPS controller. Through Simulink/Stateflow of PEPS controller using logic system modeling, the PEPS controller complex system functions are divided into different function layers with each functional layer modeling respectively, and implement logic function design by the graphical language.

Modeling techniques matter a lot in many fields of engine engineering. Models are requested not only for control design but also for dynamic prediction. However, problems might be encountered during modeling process either because of the system complexity or the unaffordable modeling cost. As a result, a new modeling technique based on disturbance estimation is proposed in this paper. By employing the proposed modeling technique, models are set up in real time with the online information from input and output. The uncertainties of system dynamics are handled as internal disturbance of the system, while the perturbation from outside are taken as the external disturbance, and the combination of the two can be estimated online by a kind of active observer called extended state observer (ESO).

We developed “Two-Stage Method” that makes it possible to evaluate the automotive suitability of FM receivers by generating a virtual radio wave environment on a PC. The major technological challenge for the Two-Stage Method was reproducing an actual radio wave environment on PC. It was necessary to estimate the characteristics of the FM radio wave environment in tests using the Multiple Signal Classification (MUSIC) method. However, when the MUSIC method is applied to FM reception, restrictions in factors including the number of array antenna elements and the occupied bandwidth result in issues of separation performance in relation to multipath waves in urban environments. We therefore developed a MUSIC Method using a virtual array antenna, making it possible to create combinations of numbers of array and sub-array elements as desired, thus boosting multipath wave separation performance. This development was reported at the 2015 SAE World Congress.

Health Ready Components are essential to unlocking the potential of Integrated Vehicle Health Management (IVHM) as it relates to real-time diagnosis and prognosis in order to achieve lower maintenance costs, greater asset availability, reliability and safety. IVHM results in reduced maintenance costs by providing more accurate fault isolation and repair guidance. IVHM results in greater asset availability, reliability and safety by recommending preventative maintenance and by identifying anomalous behavior indicative of degraded functionality prior to detection of the fault by other detection mechanisms. The cost, complexity and effectiveness of the IVHM system design, deployment and support depend, to a great extent, on the degree to which components and subsystems provide the run-time data needed by IVHM and the design time semantic data to allow IVHM to interpret those messages.

New challenges and complexities are continuously increasing in advanced driver assistance systems (ADAS) development (e.g. active safety, driver assistant and autonomous vehicle systems). Therefore, the health management of ADAS’ components needs special improvements. Since software contribution in ADAS’ development is increasing significantly, remote diagnosis and maintenance for ADAS become more important. Furthermore, it is highly recommended to predict the remaining useful life (RUL) for the prognosis of ADAS’ safety critical components; e.g. (Ultrasonic, Cameras, Radar, LIDAR). This paper presents a remote diagnosis, maintenance and prognosis (RDMP) framework for ADAS, which can be used during development phase and mainly after production. An overview of RDMP framework’s elements is explained to demonstrate how/when this framework is connected to database servers and remote analysis servers.

Electronics now control or drive a large part of automotive system design and development, from audio system enhancements to improvements in engine and drive-train performance, and innovations in passenger safety. Industry estimates suggest that electronic systems account for more than 30% of the cost of a new automobile and represent approximately 90% of the innovations in automotive design. As electronic content increases, so does the possibility of electronic system failure and the potential for compromised vehicle safety. Even when designed properly, electronics can be the weakest link in automotive system performance due to variations in component reliability and environmental conditions. Engineers need to understand worst-case system performance as early in the design process as possible.

The CAN FD protocol internationally standardized in ISO 11898-1:2015 just describes how to implement it into silicon. The ISO 11898-2:2016 standard specifies the physical media attachment (PMA) sub-layer of the CAN (FD) physical layer. The design of CAN FD networks is not in the scope of these standards. In general, the physical layer design of CAN FD networks requires more attention compared with Classical CAN networks. First recommendations have been developed. Different standardization bodies have already specified or are in the process of specifying higher-layer protocols, for example ISO for on-board diagnostic, ASAM for calibration, etc.

Wire shorts on an in-vehicle controller area network (CAN) impact the communication between electrical control units (ECUs), and negatively affects the vehicle control. The fault, especially the intermittent fault, is difficult to locate. In this paper, an equivalent circuit model for in-vehicle CAN bus is developed under the wire short fault scenario. The bus resistance is estimated and a resistance-distance mapping approach is proposed to locate the fault. The proposed approach is implemented in an Arduino-based embedded system and validated on a vehicle frame. The experimental results are promising. The approach presented in this paper may reduce trouble shooting time for CAN wire short faults and may enable early detection before the customer is inconvenienced.

This paper presents a custom integrated circuit (IC) on which circuit functions necessary for “Active Hydraulic Brake (AHB) system” are integrated, and its key component, “Current-to-Digital Converter” for solenoid current measurement. The AHB system, which realizes a seamless brake feeling for Antilock Brake System (ABS) and Regenerative Brake Cooperative Control of Hybrid Vehicle, and the custom IC are installed in the 4th-generation Prius released in 2015. In the AHB system, as linear solenoid valves are used for hydraulic brake pressure control, high-resolution and high-speed sensing of solenoid current with ripple components due to pulse width modulation (PWM) is one of the key technologies. The proposed current-to-digital converter directly samples the drain-source voltage of the sensing DMOS (double-diffused MOSFET) with an analog-to-digital (A/D) converter (ADC) on the IC, and digitizes it.

Connectivity has become an essential need for daily device users. With the car projected to be the “ultimate mobile device”, connectivity modules will eventually be mainstream in every car. Network providers are expanding their infrastructure and technology to accommodate the connected cars. Besides making voice and emergency calls the connected car will be sharing data with telematics service providers, back end systems and other vehicles. This trend will increase vehicle modules, complexity, entry points and vulnerabilities. This paper will present the current connected car architectures. The paper will present current architectural issues of the connected car and its vulnerabilities. The paper will present a new proposed architecture for the future connected car that enhances efficiency and security.

The suitability of FM radio receivers for automobiles has conventionally been rated by evaluating reception characteristics for broadcast waves in repeated driving tests in specific test environments. The evaluation of sound quality has relied on the auditory judgment due to difficulties to conduct quantitative evaluations by experiments. Thus the method had issues in terms of the reproducibility and objectivity of the evaluations. To address these issues, a two-stage method generating a virtual radio wave environment on a PC was developed. The research further defined the multipath distortion rate, MDr, as an index for the sound quality evaluation of FM receivers, and the findings concerning the suitability of the evaluation of FM terminals for automobiles were reported at the 2015 SAE World Congress.

Recently, the electromagnetic interference in an AM radio by the noise generated from a power control unit (DC-DC converters, inverters) in a hybrid vehicle (HV) has become a serious problem. To solve the problem, most noise suppression methods, for example, use noise filters for noise sources and shield wiring and ferrite cores for noise propagation paths. In this paper, we propose a noise suppression method using the digital signal processing in an AM radio receiver. In this method, first the receiving AM radio signal containing HV noise is quadrature demodulated. Next, a replica signal of the noise is generated by using the noise signal in the quadrature component. Then, the replica signal is subtracted from the AM radio signal containing the noise of the in-phase component. We construct a prototype of the radio receiver system based on this method and demonstrate that the system can reduce the HV noise superimposed on the AM radio signal by more than 20 dB.

In this paper, a consensus framework for cooperative parameter estimation within the vehicular network is presented. It is assumed that each vehicle is equipped with a dedicated short range communication (DSRC) device and connected to other vehicles. The improvement achieved by the consensus for parameter estimation in presence of sensor’s noise is studied, and the effects of network nodes and edges on the consensus performance is discussed. Finally, the simulation results of the introduced cooperative estimation algorithm for estimation of the unknown parameter of road condition is presented. It is shown that due to the faster dynamic of network communication, single agents’ estimation converges to the least square approximation of the unknown parameter properly.

The rapid increase in the sophistication of vehicle automation demands development of evaluation protocols tuned to understanding driver-automation interaction. Driving simulators provide a safe and cost-efficient tool for studying driver-automation interaction, and this paper outlines general considerations for simulator-based evaluation protocols. Several challenges confront automation evaluation, including the limited utility of standard measures of driver performance (e.g., standard deviation of lane position), and the need to quantify underlying mental processes associated with situation awareness and trust. Implicitly or explicitly vehicle automation encourages drivers to disengage from driving and engage in other activities. Thus secondary tasks play an important role in both creating representative situations for automation use and misuse, as well as providing embedded measures of driver engagement.

In this paper, we present a model predictive controller for the autonomous vehicle lane-change maneuver. Firstly, an optimal trajectory is generated by polynomial, then, utilize it as the reference trajectory of the controller. It is well known that vehicle with nonholonomic constraints can not be feedback stabilized through continuously differentiable, time-invariant control laws. One of the advantages of MPC is the ability to handle constraints in a straightforward way. Quadratic programming is used to solve a linear MPC by successive linearization of an error model of the vehicle. Due to that the vehicle dynamics model is used, in order to prevent optimal solution cannot be obtained within the prescribed time, the relaxation factor in the objective function.