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Instrument Panel Cluster (IPC), is a key ECU in vehicles. As IPC is a visual product, testing the software features of IPC is highly manual effort. Software Testing constitutes for approx. 35% of the total Software Development Life Cycle (SDLC). High focus on quick to market, shorter SDLC coupled with manual validation environment poses a challenge of increasing testing efficiency and improving software quality. This challenge drove the need to investigate a solution to automate the testing process and cut down the huge manual effort that goes into validating an Instrument Panel Cluster (IPC) software. The proposed intrusive and non-intrusive approaches to automate the testing process of IPC software employs a Frame Grabbing technique for the former approach and a Camera based technique for the latter. Both the approaches are robust, reliable, and scalable and covers the major portion of Vehicle Instrument cluster test scenarios.

Research of Adaptive Cruise Control (ACC) is an important issue of intelligent vehicle (IV). As we all known, a real and experienced driver can control vehicle's speed very well under every traffic environment of ACC working. So a direct and feasible way for establishing ACC controller is to build a human-like longitudinal control algorithm with the simulation of driver behavior of speed control. In this paper, a novel fuzzy self-tuning control algorithm of ACC is established and this controller's parameters can be tuned on-line based on the evaluation indexes that can describe how the driver consider the quality of dynamical characteristic of vehicle longitudinal dynamics. With the advantage of the controller's parameter on-line self-tuning, the computational workload from matching design of ACC controller is also efficiently reduced.

A HIL simulator for developing vehicle adaptive cruise control systems is presented in this paper. The xPC target is used to establish real-time simulation environment. The simulator is composed of a virtual vehicle model, real components of an ACC system like ECU, electronic throttle and braking modulator, a user interface to facilitate simulation, and brake and accelerator pedals to make interactive driver inputs easier. The vehicle model is validated against data from field test. Tests of an ACC controller in the real-time are conducted on the simulator.

The crush performance of lightweight composite automotive structures varies significantly between static and dynamic test conditions. This paper discusses the development of a new dynamic testing facility that can be used to characterize crash performance at high loads and constant speed. Previous research results from the Energy Management Working Group (EMWG) of the Automotive Composites Consortium (ACC) showed that the static crush resistance of composite tubes can be significantly greater than dynamic crush results at speeds greater than 2 m/s. The new testing facility will provide the unique capability to crush structures at high loads in the intermediate velocity range. A novel machine control system was designed and projections of the machine performance indicate its compliance with the desired test tolerances. The test machine will be part of a national user facility at the Oak Ridge National Laboratory (ORNL) and will be available for use in the summer of 2002.

The conventional radar modeling methods for automotive applications were either function-based or physics-based. The former approach was mainly abstracted as a solution of the intersection between geometric representations of radar beam and targets, while the latter one took radar detection mechanism into consideration by means of “ray tracing”. Although they each has its unique advantages, they were often unrealistic or time-consuming to meet actual simulation requirements. This paper presents a combined geometric and physical modeling method on millimeter-wave radar systems for Frequency Modulated Continuous Wave (FMCW) modulation format under a 3D simulation environment. With the geometric approach, a link between the virtual radar and 3D environment is established. With the physical approach, on the other hand, the ideal target detection and measurement are contaminated with noise and clutters aimed to produce the signals as close to the real ones as possible.

Vehicle lane keeping system is becoming a new research focus of drive assistant system except adaptive cruise control system. As we all known, vehicle lateral dynamics show strong nonlinear and time-varying with the variety of longitudinal velocity, especially tire’s mechanics characteristic will change from linear characteristic under low speed to strong nonlinear under high speed. For this reason, the traditional PID controller and even self-tuning PID controller, which need to know a precise vehicle lateral dynamics model to adjust the control parameter, are too difficult to get enough accuracy and the ideal control quality. Based on neural network’s ability of self-learning, adaptive and approximate to any nonlinear function, an adaptive PID control algorithm with BP neural network self-tuning online was proposed for vehicle lane keeping.

For urea Selective Catalytic Reduction (SCR) systems, adaptive control is of interest to provide a capability of maintaining high NOx conversion efficiency and low ammonia slip in the presence of uncertainties in the system. In this paper, the dynamics of the urea SCR system are represented by a control-oriented model which is based on a linear transfer function, with parameters dependent on engine operating conditions. The parameters are identified from input-output data generated by a high fidelity full chemistry model of the urea SCR system. The use of the full chemistry model facilitated the representation of the dynamics of stored ammonia (not a directly measurable parameter) as well as post SCR NOx and ammonia slip. A closed-loop Proportional-plus-Integral (PI) controller was first designed using the estimate of stored ammonia as a feedback signal.

The continued increase in complexity of automotive electronics has further necessitated for systems to be designed for optimal testing and servicing in the field. Locating failures within complex, interactive electronic systems can create conditions of both high warranty costs and customer dissatisfaction. Decisions about levels of system integration and diagnostics early in the design phases are fundamental parts of these considerations and are addressed in this paper. The approach focuses on projecting field repair rates and maintenance costs using a Monte Carlo computer simulation method given various component parameters such as part costs, reliability, labor time, and field diagnostic strategies. Results of the projection technique were shown to be quite accurate in projecting field warranty costs of a complex electronic system.

For many years, carmakers have developed unique system designs to gain a competitive advantage using some unique technology or an optimization of a design to cut costs or improve quality. This leads to continual increase in complexity, long development times and high development costs. A common platform, based on an "open architecture,'' provides a solution for many of the problems associated with the conventional automotive approach to electrical/electronic system designs. The PC industry is a prime example of how an open architecture can provide benefits to the consumer, manufacturers of software and hardware components, as well as complete system integrators. The PC, based on the initial IBM computer developed in the early eighties, has become a de facto standard that has survived 20 years of fast and dramatic changes in the fundamental technologies used within the platform.

The global adaptive cruise control (ACC) market is expected to witness a compound annual growth rate of 18.3% during the forecast period to reach $15,290 million by 2023 [1]. The driver uses an ACC system to reduce the driving burden and improve safety. The ACC mode in a car is fixed, but different drivers have different driving habits. This paper will verify this through experiments and divide drivers into three categories according to the drivers’ driving habits. Therefore, we will design a personalized ACC, wherein an ACC system, under the same working conditions, can have different acceleration and deceleration to meet the needs of different types of drivers. Therefore, this paper collects driver data, analyzes model data and identifies its parameters, and finally verifies the different effects of personalized ACC through simulation.

The diesel particulate filters (DPF) are considered the most robust technologies for particle emission reduction both in terms of mass and number. On the other hand, the increase of the backpressure in the exhaust system due to the accumulation of the particles in the filter walls leads to an increase of the engine fuel consumption and engine power reduction. To limit the filter loading, and the backpressure, a periodical regeneration is needed. Because of the growing interest about particle emission both in terms of mass, number and size, it appears important to monitor the evolution of the particle mass and number concentrations and size distribution during the regeneration of the DPFs. For this matter, in the presented work the regeneration of a catalyzed filter was fully analyzed. Particular attention was dedicated to the dynamic evolution both of the thermodynamic parameters and particle emissions.

Casting is the ability to let users transfer their favorite videos, music, movies, etc. from their phone to a chosen display. This functionality has become very popular these days, and to the user, it is as simple as clicking a button. This “simple” task is a complex system that requires various independent sources to communicate efficiently and effectively to produce a robust and reliable output. The sending and receiving devices are required to be on the same network - which involves reliable and secure connection. This allows the sending of the URL of the chosen feature to the server provider, which will then connect to the receiver embedded electronics where the authentication process that protects Digital Rights Management (DRM) is established. In the era of developing autonomous and luxury vehicles, this technology has the potential to add a new dimension of in-vehicle entertainment that could come very close to the home experience.

To achieve high robustness and quality, automotive ECUs must initialize from low-power states as quickly as possible. However, microprocessor and memory advances have failed to keep pace with software image size growth in complex ECUs such as in Infotainment and Telematics. Loading the boot image from non-volatile storage to RAM and initializing the software can take a very long time to show the first screen and result in sluggish performance for a significant time thereafter which both degrade customer perceived quality. Designers of mobile devices such as portable phones, laptops, and tablets address this problem using Suspend mode whereby the main processor and peripheral devices are powered down during periods of inactivity, but memory contents are preserved by a small “self-refresh” current. When the device is turned back “on”, fully initialized memory content allows the system to initialize nearly instantaneously.

Hardware-in-the-loop (HiL) simulation is an advanced technique for development and testing of complex real-time embedded systems. This technique has greatly developed in the last decades and has been more and more used in the automotive industry for algorithm and software development, hardware validation, safety validation, and fault investigation activities. Plant simulation model executes in HiL simulator to provide a virtual vehicle that interacts in an open-loop or closed-loop fashion with the embedded system that is under test. Compared to in-vehicle testing, HiL simulation provides benefits of low cost, high availability, high flexibility, repeatability, and test automation capability. HiL simulation reduces the risk caused by control failure, which is especially important for self-driving control system development and testing. The HiL simulation system is more application specific.

In this paper, we compare controllers for the electronic throttle and variable geometry turbocharger in boosted stoichiometric gasoline direct injection engines. The control objectives are fast response and small overshoot of the intake manifold pressure. The problem is treated within the multi-objective optimization framework, applied to a simulation model of the engine. Pareto optimal fronts are constructed for each of the controllers and compared to each other. The best controller is thereby identified and further options to improve its response via preview-based control are discussed.

Modern automotive manufacturing and after-sale service environments require tailoring of configuration values or “calibrations” within the vehicle’s various electronic control units (ECUs) to that vehicle’s specific option content. Historically, ECU hardware and software limitations have led designers to implement calibratable values using opaque binary blocks tied directly to ECU internal software data structures. Such coupling between calibration data files and ECU software limits traceability and reuse across different software versions and ECU variants. However, more and more automotive ECUs are featuring fast microprocessors, large memories, and preemptive, multi-tasking operating systems that open opportunities to object-oriented approaches. This paper presents the CalDef system for automotive ECU calibration software architecture. CalDef uses XML database methods to define, develop, and deliver calibration values as objects in both manufacturing and service environments.

The intelligent unmanned ground vehicle (UGV) motorcade system consisting of one leader and n − 1 followers is considered. The safety distance between the front and rear UGVs is treated as the control target. Since the safety distance constraint is a unilateral constraint, the state transformation is needed. Hence, a piecewise type conversion function is formulated to serve for the transformation of the original inequality constraint. The system equation is further expressed by the new state. We assume that the input of the leading UGV is known. Combined with the uncertainty evaluation, a class of collaborative controls for the following UGVs is proposed to deal with the uncertainty with unknown bound. The effectiveness of the designed control is verified by both Lyapunov stability theory and simulations. Both theoretical and simulation results illustrate that the longitudinal safety, stability and global behavior of the intelligent motorcade system are guaranteed.

In recent years, rapid and significant advances in fuel cell technology, together with advances in power electronics and control methodology, has enabled the development of high performance fuel cell powered electric vehicles. A key advance is that the low temperature (80°C) proton-exchange-membrane (PEM) fuel cell has become mature and robust enough to be used for automotive applications. Apart from the apparent advantage of lower vehicle emission, the overall fuel cell vehicle static and dynamic performance and power and energy efficiency are critically dependent on the intelligent design of the control systems and control methodologies. These include the control of: fuel cell heat and water management, fuel (hydrogen) and air (oxygen) supply and distribution, electric drive, main and auxiliary power management, and overall powertrain and vehicle systems.

The electronic control system of the variable nozzle turbocharger (VNT) was designed. The actuator is the electro-hydraulic servo proportional solenoid. The signals of the engine pedal position sensor, the engine speed sensor, the boost pressure sensor, the intake air temperature sensor, and the ambient pressure sensor are sampled and filtered. The engine working condition is estimated. The control algorithm was designed as the closed-loop feedback digital PI control together with the open-loop feed forward control. The gain-scheduled PI control method is applied to improve the robustness. The control system was calibrated at the turbocharger test bench and the engine test bench. The results indicate the designed control system has good performance for the boost pressure control under the steady and transient conditions.

Automotive display designers are faced with the task of providing more information to the driver through the implementation of an increased amount of on-board vehicle electronic systems. Package space in and around the instrument panel however, is at a premium. One remedy to this situation is the implementation of a dot matrix display with enough flexibility to fulfill several potential applications. Once a dot matrix display is integrated into a vehicle, information can be reformatted for presentation to the driver without redesigning the display device or its associated electronics. The system designer can then concentrate development resources on the remaining display subsystem components and issues such as user interface, display lighting, and packaging requirements for a specific application.