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Efficient integration of mechanics and microelectronics components is nowadays a must within the automotive industry in order to minimize integration risks and support optimization of the entire system. We propose in this work a cross domain co-simulation platform for the efficient analysis of mechatronic systems. The interfacing of two state-of-the-art simulation platforms provides a direct link between the two domains at an early development stage, thus enabling the validation and optimization of the system already during modeling phase. The proposed cross-domain co-simulation is used within our TEODACS project for the analysis of the FlexRay technology. We illustrate using a drive-by-wire use case how the different architecture choices may influence the system.

Automotive embedded systems have become very complex, are strongly integrated, and the safety-criticality and real-time constraints of these systems raise new challenges. The OSEK/VDX standard provides an open-ended architecture for distributed real-time capable units in vehicles. This is supported by the OSEK Implementation Language (OIL), a language aiming at specifying the configuration of these real-time operating systems. The challenge, however, is to ensure consistency of the concept constraints and configurations along the entire product development. The contribution of this paper is to bridge the existing gap between model-driven systems engineering and software engineering for automotive real-time operating systems (RTOS). For this purpose a bidirectional tool bridge has been established based on OSEK OIL exchange format files.

With the increasing number of urban cars, parking has become the primary problem that people face in daily life. Therefore, many scholars have studied the automatic parking system. In the existing research, most of the path planning methods use the combined path of arc and straight line. In this method, the path curvature is not continuous, which indirectly leads to the low accuracy of path tracking. The parking path designed using the fifth-order polynomial is continuous, but its curvature is too large to meet the steering constraints in some cases. In this paper, a continuous-curvature parking path is proposed. The parking path tracker based on Model Predictive Control (MPC) algorithm is designed under the constraints of the control accuracy and vehicle steering. Firstly, in order to make the curvature of the parking path continuous, this paper superimposes the fifth-order polynomial with the sigmoid function, and the curve obtained has the continuous and relatively small curvature.

Experimental studies of soot particles showed that the intensity ratio of amorphous and graphite layers measured by Raman spectroscopy correlates to soot oxidation reactivities, which is very important for regeneration of the diesel particulate filters and gasoline particulate filters. This physical mechanism is absent in all soot models. In the present paper, a novel two-layer soot model was proposed that considers the amorphous and graphite layers in the soot particles. The soot model considers soot inception, soot surface growth, soot oxidation by O2 and OH, and soot coagulation. It is assumed that amorphous-type soot forms from fullerene. No soot coagulation is considered in the model between the amorphous- and graphitic-types of soot. Benzene is taken as the soot precursor, which is formed from acetylene. The model was implemented into a commercial CFD software CONVERGE using user defined functions. A diesel engine case was simulated.

Increasing demands for safety, security, and certifiability of embedded automotive systems require additional development effort to generate the required evidences that the developed system can be trusted for the application and environment it is intended for. Safety standards such as ISO 26262 for road vehicles have been established to provide guidance during the development of safety-critical systems. The challenge in this context is to provide evidence of consistency, correctness, and completeness of system specifications over different work-products. One of these required work-products is the hardware-software interface (HSI) definition. This work-product is especially important since it defines the interfaces between different technologies. Model-based development (MBD) is a promising approach to support the description of the system under development in a more structured way, thus improving resulting consistency.

Automotive electronics are complex distributed embedded systems. The tight interconnection of the different functionalities (e.g. ABS, ESP) makes the network resource the backbone of the system. Time-triggered architectures and time-triggered communication systems such as FlexRay have been introduced in this context to support the development and integration of safety-relevant systems. An important enhancement to this approach is online monitoring and transparent diagnosis to ensure better assessment of the system status (faster fault detection) during operation. This is required for preventive maintenance in order to improve system availability. We propose a non-intrusive two steps method for the analysis of the communication architecture. In the first step, the system behavior is monitored at different abstraction levels by a dedicated tester node. The traces are analyzed online and the current system behavior is compared to the specification (e.g.

This paper is part of the European OWHEEL project. It proposes a method to improve the comfort of a vehicle by adaptively controlling the Camber and Toe angles of a rear suspension. The purpose is achieved through two actuators for each wheel, one that allows to change the Camber angle and the other the Toe angle. The control action is dynamically determined based on the error between the reference angle and the actual angles. The reference angles are not fixed over time but dynamically vary during the maneuver. The references vary with the aim of maintaining a Camber angle close to zero and a Toe angle that follows the trajectory of the vehicle during the curve. This improves the contact of the tire with the road. This solution allows the control system to be used flexibly for the different types of maneuvers that the vehicle could perform. An experimentally validated sports vehicle has been used to carry out the simulations. The original rear suspension is a Trailing-arm suspension.

The automotive domain has seen safety engineering at the forefront of the industry’s priorities for the last decade. Therefore, additional safety engineering efforts, design approaches, and well-established safety processes have been stipulated. Today many connected and automated vehicles are available and connectivity features and information sharing are increasingly used. This increases the attractiveness of an attack on vehicles and thus introduces new risks for vehicle cybersecurity. Thus, just as safety became a critical part of the development in the late 20th century, the automotive domain must now consider cybersecurity as an integral part of the development of modern vehicles. Aware of this fact, the automotive industry has, therefore, recently taken multiple efforts in designing and producing safe and secure connected and automated vehicles.

One main challenge during the validation of automotive communication architectures is to consider the assembled system and more especially the interactions between the different components. We propose in this work a test and validation infrastructure based on tightly coupled co-simulation and prototype platforms. The co-simulation framework, on one hand, enables the efficient simulation of the entire network and the accurate analysis of the communication at different abstraction layers. On the other hand, the prototype framework is required for the model calibration and for the system validation on a realistic environment. We discuss further how the interconnection of these two platforms supports the analysis of both single components and entire communication networks. Experimental results illustrate our approach.

As one of advanced driver assistance systems (ADAS), automatic parking system has great market prospect and application value. In this paper, based on an intelligent vehicle platform, an automatic parking system is designed by using multi-point preview theory. The vehicle kinematics model was established, based on Ackermann steering principle. By analyzing working conditions of parallel parking, complex constraint condition of parking trajectory is established and reference trajectory based on sine wave is proposed. In addition, combined with multi-point preview theory, the design of trajectory following controller for automatic parking is completed. The cost function is designed, which consider the trajectory following effect and the degree of easy handling. The optimization of trajectory following control is completed by using the cost function.

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.

Driving assistance system is regarded as an effective method to improve driving safety and comfort and is widely used in automobiles. However, due to the different driving styles of different drivers, their acceptance and comfort of driving assistance systems are also different, which greatly affects the driving experience. The key to solving the problem is to let the system understand the driving style and achieve humanization or personalization. This paper focuses on clustering and identification of different driving styles. In this paper, based on the driver's real vehicle experiment, a driving data acquisition platform was built, meanwhile driving conditions were set and drivers were recruited to collect driving information. In order to facilitate the identification of driving style, the correlation analysis of driving features is conducted and the principal component analysis method is used to reduce the dimension of driving features.

The presented paper is dedicated to the driving comfort evaluation in the case of the electric vehicle architecture with four independent wheel corners equipped with in-wheel motors (IWMs). The analysis of recent design trends for electrified road vehicles indicates that a higher degree of integration between powertrain and chassis and the shift towards a corner-based architecture promises improved energy efficiency and safety performances. However, an in-wheel-mounted electric motor noticeable increases unsprung vehicle mass, leading to some undesirable impact on chassis loads and driving comfort. As a countermeasure, a possible solution lies in integrated active corner systems, which are not limited by traditional active suspension, steer-by-wire and brake-by-wire actuators. However, it can also include actuators influencing the wheel positioning through the active camber and toe angle control.

Battery electric vehicles (BEV) share the ability of regenerative braking since they are equipped with two independent types of deceleration devices, namely the electric motor working as a generator and the friction brakes. Correct interaction of these systems in terms of driving safety and energy efficiency is a function of the Brake Blending Control. Individual electric motors for each wheel and a decoupled brake system provides the Brake Blending with a high design flexibility that allows significant advantages regarding energy consumption, brake performance, and driving comfort. This paper is focusing on the fail behaviour and analyses the robustness and redundancy abilities of such systems against various error scenarios. For this purposes, a distributed x-in-the-loop environment, consisting of dedicated simulation and hardware testing components, is introduced.

Brake-by-wire (BBW) system has drawn a great attention in recent years as driven by rapidly increasing demands on both active brake controls for intelligent vehicles and regenerative braking controls for electric vehicles. However, unlike conversional brake systems, the reliability of the brake-by-wire systems remains to be challenging due to its lack of physical connection in case of system failure. There are various causes for the failure of a BBW system, such as failure of brake controller, loss of sensor signals, failure of communication or even power supply, to name a few. This paper presents a fault-tolerant control under novel control architecture. The proposed control architecture includes a driver command interpreter module, a command integration module, a control allocation module, a fault diagnosis module and state observers. The fault-tolerant control is designed based on a quadratic optimal control method with consideration of actuator constraints.

This paper presents a unified novel function-based brake control architecture, which is designed based on a top-down approach with functional abstraction and modularity. The proposed control architecture includes a commands interpreter module, including a driver commands interpreter to interpret driver intention, and a command integration to integrate the driver intention with senor-guided active driving command, state observers for estimation of vehicle sideslip, vehicle speed, tire lateral and longitudinal slips, tire-road friction coefficient, etc., a commands integrated control allocation module which aims to generate braking force and yaw moment commands and provide optimal distribution among four wheels without body instability and wheel lock or slip, a low-level control module includes four wheel pressure control modules, each of which regulates wheel pressure by fast and accurate tracking commanded wheel pressure.

Adaptive cruise control (ACC), as one of the advanced driver assistance systems (ADAS), has become increasingly popular in improving both driving safety and comfort. Since the objectives of ACC can be multi-dimensional, and often conflict with each other, it is a challenging task in its control design. The research presented in this paper takes ACC control design as a constrained optimization problem with multiple objectives. A hierarchical framework for ACC control is introduced, aimed to achieve optimal performance on driving safety and comfort, speed and/or distance tracking, and fuel economy whenever possible. Under the hierarchical framework, the operational mode is determined in the upper layer, in which a model predictive control (MPC) based spacing controller is employed to deal with the multiple control objectives. On the other hand, the lower layer is for actuator control, such as braking and driving control for vehicle longitudinal dynamics.

An important problem of recent active safety applications is data acquisition for parameters of tire-road interaction, especially coefficient of friction or specific forces in contact patch. Analysis of present solutions in this field allows setting off the virtual and hardware-based determination of tire grip properties. The virtual procedures can be subclassified into Dynamics simulation method Statistical method Fuzzy logic method. The hardware-based procedures are connected with On-board sensors of direct tire grip measurement On-board sensors of indirect tire grip measurement Off-board (on-road) sensors. For above mentioned variants the appropriate engineering solutions are considered in the paper. The long-term approach in road identification centers on active safety applications with on-road sensors, which are integrated in intelligent transportation systems (ITS). The paper proposes conceptual structure for this system.

Battery-electric vehicles (BEVs) require new chassis components, which are realized as mechatronic systems mainly and support more and more by-wire functionality. Besides better controllability, it eases the implementation of integrated control strategies to combine different domains of vehicle dynamics. Especially powertrain layouts based on electric in-wheel machines (IWMs) require such an integrated approach to unfold their full potential. The present study describes an integrated, longitudinal vehicle dynamics control strategy for a battery electric sport utility vehicle (SUV) with an electric rear axle based on in-wheel propulsion. Especially the influence of electronic brake force distribution (EBD) and torque blending control on the overall performance are discussed and demonstrated through experiments and driving cycles on public road and benchmarked to results of previous studies derived from [1].

The replacement of safety-critical mechanical components with electro-mechanical systems has led to the fact that safety aspects play a central role in development of embedded automotive systems. Recently, consumer demands for connectivity (e.g., infotainment, car-2-car or car-2-infrastructure communication) as well as new advances toward advanced driver assistance systems (ADAS) or even autonomous driving functions make cybersecurity another key factor to be taken into account by vehicle suppliers and manufacturers. Although these can capitalize on experiences from many other domains, they still have to face several unique challenges when gearing up for specific cybersecurity challenges. A key challenge is related to the increasing interconnection of automotive systems with networks (such as Car2X). Due to this connectivity, it is no longer acceptable to assume that safety-critical systems are immune to security risks.