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The (Vehicle Inertia Parameter Evaluation Rig) VIPER II is a full vehicle mass and inertia parameter measurement machine. The VIPER II expands upon the capabilities of its predecessor and is capable of measuring vehicles with a mass of up to 45,360 kg (100,000 lb), an increase in capacity of 18,100 kg (40,000 lb). The VIPER II also exceeds its predecessor in both the length and width of vehicles it can measure. The VIPER II's maximum vehicle width is 381 cm (150 in) an increase of 76 cm (30 in) and maximum distance from the vehicle CG to the outer most axle is 648 cm (255 in) an additional 152 cm (60 in) The VIPER II is capable of performing measurements including vehicle CG height, pitch, roll, and yaw moments of inertia and the roll/yaw cross product of inertia. While being able to measure both heavier and larger vehicles, the VIPER II is designed to maintain a maximum error of 3% for all inertia measurements and 1% for CG height.

This paper describes the design and implementation of the SEA, Ltd. Brake and Throttle Robot (BTR). Presented are the criteria used in the initial design and the development and testing of the BTR, as well as some test results achieved with the device. The BTR is designed for use in automobiles and light trucks. It is based on a servomotor driven ballscrew, which in turn operates either the brake or accelerator. It is easily portable from one vehicle to another and compact enough to fit even smaller vehicles. The BTR is light enough so as to have minimal effect on the measurement of vehicle parameters. The BTR is designed for use as a stand-alone unit or as part of a larger control system such as the Automated Test Driver (ATD) yet allows for the use of a test driver for safety, as well as test selection, initiation, and monitoring. Installation in a vehicle will be described, as well as electronic components that support the BTR.

The assessment of fuel economy of new vehicles is typically based on regulatory driving cycles, measured in an emissions lab. Although the regulations built around these standardized cycles have strongly contributed to improved fuel efficiency, they are unable to cover the envelope of operating and environmental conditions the vehicle will be subject to when driving in the “real-world”. This discrepancy becomes even more dramatic with the introduction of Connectivity and Automation, which allows for information on future route and traffic conditions to be available to the vehicle and powertrain control system. Furthermore, the huge variability of external conditions, such as vehicle load or driver behavior, can significantly affect the fuel economy on a given route. Such variability poses significant challenges when attempting to compare the performance and fuel economy of different powertrain technologies, vehicle dynamics and powertrain control methods.

Vehicle dynamics models employed in heavy truck simulation often treat the semitrailer as a torsionally rigid member, assuming zero deflection along its longitudinal axis as a moment is applied to its frame. Experimental testing, however, reveals that semitrailers do twist, sometimes enough to precipitate rollover when a rigid trailer may have remained upright. Improving the model by incorporating realistic trailer roll stiffness values can improve assessment of heavy truck dynamics, as well as an increased understanding of the effectiveness of stability control systems in limit handling maneuvers. Torsional stiffness measurements were conducted by the National Highway Traffic Safety Administration (NHTSA) for eight semitrailers of different types, including different length box vans, traditional and spread axle flat beds, and a tanker.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

Many automotive components and sub-systems require viscoelastic damping treatments to control noise and vibration characteristics. To aid the dynamic design process, new approaches are needed for modeling of partial damping treatments and characterization of the overall dynamic behavior. The analytical component of the design process is illustrated via the transmission casing cover, along with supporting experiments. First, the vibration response of production casing plates is examined, with and without the constrained layer treatment. A modified flat plate is employed along with a generic housing that provides the realistic boundary conditions for subsequent work. A simplified analytical damping model for constrained viscoelastic layer damping is suggested based on assumed modal functions. Using the analytical model, design guidelines in terms of optimal patch shapes and locations are suggested.

A determination of the vehicle states and tire forces is critical to the stability of vehicle dynamic behavior and to designing automotive control systems. Researchers have studied estimation methods for the vehicle state vectors and tire forces. However, the accuracy of the estimation methods is closely related to the employed model. In this paper, tire lag dynamics is introduced in the model. Also application of estimation methods in order to improve the model accuracy is presented. The model is developed by using the global searching algorithm, a Genetic Algorithm, so that the model can be used in the nonlinear range. The extended Kalman filter and sliding mode observer theory are applied to estimate the vehicle state vectors and tire forces. The obtained results are compared with measurements and the outputs from the ADAMS full vehicle model. [15]

This year, in the third year of FutureTruck competition, the Ohio State University team has taken the challenge to convert a 2002 Ford Explorer into a more fuel efficient and environmentally friendly SUV. This goal was achieved by use of a post-transmission, charge sustaining, parallel hybrid diesel-electric drivetrain. The main power source is a 2.5-liter, 103 kW advanced CIDI engine manufactured by VM Motori. A 55 kW Ecostar AC induction electric motor provides the supplemental power. The powertrain is managed by a state of the art supervisory control system which optimizes powertrain characteristics using advanced energy management and emission control algorithms. A unique driver interface implementing advanced telematics, and an interior designed specifically to reduce weight and be more environmentally friendly add to the utility of the vehicle as well as the consumer appeal.

The acoustic characteristics of a hybrid silencer consisting of two dissipative chambers and a Helmholtz resonator are investigated first computationally and experimentally. Complex wave number and characteristic impedance are used for the dissipative chambers to account for the wave propagation through absorbing material. Three-dimensional boundary element method (BEM) is employed to predict the transmission loss in the absence of mean flow and the predictions are compared with the experimental results obtained from an impedance tube setup. Noting that the long connecting tube between acoustic elements may reduce the transmission loss near the resonance frequency, two alternative hybrid silencers with short connecting tubes are also investigated by BEM. The present study shows the effectiveness of hybrid silencers over a wide frequency range and demonstrates the importance of understanding each acoustic element, as well as their interaction in designing silencers.

The single-parameter, in-process monitor and automatic control systems for the resistance spot welding process have been studied by many investigators. Some of these have already been commercialized and used by sheet metal fabricators. These control systems operate primarily on one of the three process parameters: maximum voltage or voltage drop, dynamic resistance, or thermal expansion between electrodes during nugget formation. Control systems based on voltage or dynamic resistance have been successfully implemented for industrial applications. A great amount of experience on these two control methods has been accumulated through trial-and-error approaches. The expansion-based control system is not commonly utilized due to lack of experience and understanding of the process. Since the expansion displacement between electrodes during welding responds directly to the weld nugget formation, this control parameter provides a better means to produce more precise spot welds.

A Software-in-the-Loop (SIL) simulation is presented here wherein control algorithms for the Anti-lock Braking System (ABS) and Roll Stability Control (RSC) system were developed in Simulink. Vehicle dynamics models of a 6×4 cab-over tractor and two trailer combinations were developed in TruckSim and were used for control system design. Model validation was performed by doing various dynamic maneuvers like J-Turn, double lane change, decreasing radius curve, high dynamic steer input and constant radius test with increasing speed and comparing the vehicle responses obtained from TruckSim against field test data. A commercial ESC ECU contains two modules: Roll Stability Control (RSC) and Yaw Stability Control (YSC). In this research, only the RSC has been modeled. The ABS system was developed based on the results obtained from a HIL setup that was developed as a part of this research.

Fault diagnosis for automotive systems is driven by government regulations, vehicle repairability, and customer satisfaction. Several methods have been developed to detect and isolate faults in automotive systems, subsystems and components with special emphasis on those faults that affect the exhaust gas emission levels. Limit checks, model-based, and knowledge-based methods are applied for diagnosing malfunctions in emission control systems. Incipient and partial faults may be hard to detect when using a detection scheme that implements any of the previously mentioned methods individually; the integration of model-based and knowledge-based diagnostic methods may provide a more robust approach. In the present paper, use is made of fuzzy residual evaluation and of a fuzzy expert system to improve the performance of a fault detection method based on a mathematical model of the engine.

Advances in sensor solutions in the automotive sector make it possible to develop better ADAS and autonomous driving functions. One of the main tasks of highway chauffeur and highway pilot automated driving systems is to keep the vehicle between the lane lines while driving on a pre-defined route. This task can be achieved by using camera and/or GPS to localize the vehicle between the lane lines. However, both sensors have shortcomings in certain scenarios. While the camera does not work when there are no lane lines to be detected, an RTK GPS can localize the vehicle accurately. On the other hand, GPS requires at least 3 satellite connections to be able to localize the vehicle and more satellite connections and real-time over-the-air corrections for lane-level positioning accuracy. If GPS localization fails or is not accurate enough, lane line information from the camera can be used as a backup.

This paper describes the design and development of the hardware, electronics, and software components of a state-of-the-art automated steering controller, the SEA, Ltd. ASC. The function of the ASC is to input to a vehicle virtually any steering profile with both high accuracy and repeatability. The ASC is designed to input profiles having steering rates and timing that are in excess of the limits of a human driver. The ASC software allows the user to specify steering profiles and select controller settings, including motor controller gains, through user-interface windows. This makes it possible for the test driver to change steering profiles and settings immediately after running any test maneuver. The motor controller used in the ASC offers self-contained signal input, output, and data storage capabilities. Thus, the ASC can operate as a standalone steering machine or it can be incorporated into typical existing, on-vehicle data acquisition systems.

Autonomous vehicle technology has been developing rapidly in recent years. Vehicle parametric uncertainty in the vehicle model, variable time delays in the CAN bus based sensor and actuator command interfaces, changes in vehicle sped, sensitivity to external disturbances like side wind and changes in road friction coefficient are factors that affect autonomous driving systems like they have affected ADAS and active safety systems in the past. This paper presents a robust control architecture for automated driving systems for handling the abovementioned problems. A path tracking control system is chosen as the proof-of-concept demonstration application in this paper. A disturbance observer (DOB) is embedded within the steering to path error automated driving loop to handle uncertain parameters such as vehicle mass, vehicle velocities and road friction coefficient and to reject yaw moment disturbances.

Electric vehicles (EVs) and hybrid electric vehicles (HEVs) are getting more attention in the automotive industry with the technology improvement and increasing focus on fuel economy. For EVs and HEVs, especially all-wheel drive (AWD) EVs with two electric motors powering front and rear axles separately, an accurate motor speed measurement through resolver is significant for vehicle performance and drivability requirement, subject to resolver faults including amplitude imbalance, quadrature imperfection and reference phase shift. This paper proposes a diagnostic scheme for the specific type of resolver fault, amplitude imbalance, in AWD EVs. Based on structural analysis, the vehicle structure is analyzed considering the vehicle architecture and the sensor setup. Different vehicle drive scenarios are studied for designing diagnostic decision logic. The residuals are designed in accordance with the results of structural analysis and the diagnostic decision logic.

A key enabler to maximizing the benefits from advanced powertrain technologies is to adopt a systems integration approach and develop optimized controls that consider the propulsion system and vehicle as a whole. This approach becomes essential when incorporating Advanced Driver Assistance Systems (ADAS) and communication technologies, which can provide information on future driving conditions. This may enable the powertrain control system to further improve the vehicle performance and energy efficiency, shifting from an instantaneous optimization of energy consumption to a predictive and “look-ahead” optimization. Benefits from this approach can be realized at all levels of electrification, from conventional combustion engines to hybrid propulsion systems and full electric vehicles, and at all levels of vehicle automation.

This research focused on developing a methodology for a vehicle dynamics model of a passenger vehicle outfitted with an aftermarket Automated Driving System software package using only literature and track based results. This package consisted of Autoware.AI (Autoware ®) operating on Robot Operating System 1 (ROS™) with C++ and Python ®. Initial focus was understanding the basics of ROS and how to implement test scenarios in Python to characterize the control systems and dynamics of the vehicle. As understanding of the system continued to develop, test scenarios were adapted to better fit system characterization goals with identification of system configuration limits. Trends from on-track testing were identified and paired with first-order linear systems to simulate physical vehicle responses to given command inputs. Sub-models were developed and simulated in MATLAB ® with command inputs from on-track testing.

Driver’s license examinations require the driver to perform either a parallel parking or a similar maneuver as part of the on-road evaluation of the driver’s skills. Self-driving vehicles that are allowed to operate on public roads without a driver should also be able to perform such tasks successfully. With this motivation, the S-shaped maneuverability test of the Ohio driver’s license examination is chosen here for automatic execution by a self-driving vehicle with drive-by-wire capability and longitudinal and lateral controls. The Ohio maneuverability test requires the driver to start within an area enclosed by four pylons and the driver is asked to go to the left of the fifth pylon directly in front of the vehicle in a smooth and continuous manner while ending in a parallel direction to the initial one. The driver is then asked to go backwards to the starting location of the vehicle without stopping the vehicle or hitting the pylons.