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Moir� method is useful to measure the shape and the whole-field distributions of displacement and strain of structures. There are many kinds of moir� methods such as geometric moir� method, sampling moir� method, Fourier transform moir� method, moir� interferometry, shadow moir� method and moir� topography. Grating method analyzing directly deformation of a grating without any moir� fringe pattern is considered as an extended technique of moire method. Phase analysis of the moire fringe patterns and the grating patterns provides accurate measurements of shapes or displacement and strain distributions. Some applications of these moir� methods and grating methods to dynamic shape and strain distribution measurements of a rotating tire, sub-millimeter displacement measurements from long distance for landslide prediction, real-time shape measurements with micro-meter order accuracy, etc. are shown. Presenter Yoshiharu Morimoto, Moire Institute Inc.

Real-time simulation of truck and trailer combinations can be applied to hardware-in-the-loop (HIL) systems for developing and testing electronic control units (ECUs). The large number of configuration variations in vehicle and axle types requires the simulation model to be adjustable in a wide range. This paper presents a modular multibody approach for the vehicle dynamics simulation of single track configurations and truck-and-trailer combinations. The equations of motion are expressed by a new formula which is a combination of Jourdain's principle and the articulated body algorithm. With the proposed algorithm, a robust model is achieved that is numerically stable even at handling limits. Moreover, the presented approach is suitable for modular modeling and has been successfully implemented as a basis for various system definitions. As a result, only one simulation model is needed for a large variety of track and trailer types.

The amount of software, computation and logic embedded into the vehicle systems is increasing. Testing of complex real time embedded systems using Hardware in Loop (HIL) simulations across different vehicle platforms has been a challenge. Data driven testing enables a qualitative approach to test these complex vehicle systems. It consists of a test framework wherein the test logic and data are independent of the HIL test environment. The data comprises variables used for both input values and output verification values. This data is maintained in a database or in the form of tables. Each row defines an independent test scenario. The entire test data is divided into three categories, High, Medium and Low. This feature gives the advantage of leveraging the same set of test data from Unit Level Testing phases to the Integration Test phase in the V-Cycle of software development. A data driven test approach helps the reuse of tests across vehicle platforms.

These advanced checks have resulted in development of many new diagnostic monitors, of varying types, and a whole new internal software infrastructure to handle tracking, reporting, and self-verification of OBD related items. Due to this amplified complexity and the consequences surrounding a shortfall in meeting regulatory requirements, efficient and thorough validation of the OBD system in the powertrain control software is critical. Hardware-in-the-Loop (HIL) simulation provides the environment in which the needed efficiency and thoroughness for validating the OBD system can be achieved. A HIL simulation environment consisting of engine, aftertreatment, and basic vehicle models can be employed, providing the ability for software developers, calibration engineers, OBD experts, and test engineers to examine and validate both facets of OBD software: diagnostic monitors and diagnostic infrastructure (i.e., fault memory management).

Abstract Aiming to improve the handling performance of heavy tractor semi-trailer during turning or changing lanes at high speed, a hierarchical structure controller is proposed and a hardware-in-the-loop (HIL) test bench of the electronic pneumatic braking system is developed to validate the proposed controller. In the upper controller, a Kalman filter observer based on the heavy tractor semi-trailer dynamic model is used to estimate the yaw rates and sideslip angles of the tractor and trailer. Simultaneously, a sliding mode direct yaw moment controller is developed, which takes the estimated yaw rates and sideslip angles and the reference values calculated by the three-degrees-of-freedom dynamic model of the heavy tractor semi-trailer as the control inputs. In the lower controller, the additional yaw moments of tractor and trailer are transformed into corresponding wheel braking forces according to the current steering characteristics.

Abstract Recently, electric heavy-duty tractor-trailers (EHDTTs) have assumed significance as they present an immediate solution to decarbonize the transportation sector. Hence, to illustrate the economic viability of electrifying the freight industry, a detailed numerical model to estimate the battery capacity for an EHDTT is proposed for a route between Washington, DC, to Knoxville, TN. This model incorporates the effects of the terrain, climate, vehicular forces, auxiliary loads, and payload in order to select the appropriate motor and optimize the battery capacity. Additionally, current and near-future battery chemistries are simulated in the model. Along with equations describing vehicular forces based on Newton’s second law of motion, the model utilizes the Hausmann and Depcik correlation to estimate the losses caused by the capacity offset of the batteries. Here, a Newton-Raphson iterative scheme determines the minimum battery capacity for the required state of charge.

This is a errata for 2017-01-2520.

Abstract The advancement towards development of autonomy follows either the bottom-up approach of gradually improving and expanding existing Advanced Driver Assist Systems (ADAS) technology where the driver is present in the control loop or the top-down approach of directly developing autonomous vehicle hardware and software using alternative approaches without the driver present in the control loop. Most ADAS systems today fall under the classification of SAE Level 1 which is also referred to as the driver assistance level. The progression from SAE Level 1 to SAE Level 2 or partial automation involves the critical task of merging automated lateral control and automated longitudinal control such that the tasks of steering and acceleration/deceleration are not required to be handled by the driver under certain conditions [1].

Abstract Future SAE Level 4 and Level 5 autonomous vehicles (AV) will require novel applications of localization, perception, control, and artificial intelligence technology in order to offer innovative and disruptive solutions to current mobility problems. This article concentrates on low-speed autonomous shuttles that are transitioning from being tested in limited traffic, dedicated routes to being deployed as SAE Level 4 automated driving vehicles in urban environments like college campuses and outdoor shopping centers within smart cities. The Ohio State University has designated a small segment in an underserved area of the campus as an initial AV pilot test route for the deployment of low-speed autonomous shuttles. This article presents initial results of ongoing work on developing solutions to the localization and perception challenges of this planned pilot deployment.

This technical paper collection is focused on vehicle dynamics and controls using modeling and simulation, and experimental analysis of passenger cars, heavy trucks, and wheeled military vehicles. The papers address active and passive safety systems to mitigate rollover, yaw instability and braking issues; driving simulators and hardware-in-the-loop systems; suspension kinematics and compliance, steering dynamics, advanced active suspension technologies; and tire force and moment mechanics.

This technical paper collection is focused on vehicle dynamics and controls using modeling and simulation, and experimental analysis of passenger cars, heavy trucks, and wheeled military vehicles. The papers address active and passive safety systems to mitigate rollover, yaw instability and braking issues; driving simulators and hardware-in-the-loop systems; suspension kinematics and compliance, steering dynamics, advanced active suspension technologies; and tire force and moment mechanics.

The enactment of FMVSS 126 requires specific safety performance in vehicles 4,536 Kg (10,000 pounds) or less using an Electronic Stability Control (ESC) system as standard equipment by 2011. Further, in 2012, the regulation requires vehicles that have undergone aftermarket modification to remain in compliance with the performance standard. This paper describes: • a brief overview of the standard and its implications • the collaborative approach used in the first successful approach in meeting that requirement by a lift kit manufacturer o a Hardware In the Loop (HIL) test alternative for establishing a reasonable expectation for a vehicle to demonstrate compliance after modification. • Collaborative challenges overcome: o aftermarket manufacturers seeking information sharing with OEMs and Tier One suppliers: o respecting the intellectual property of OEMs and Tier One suppliers o maintaining the integrity between tool competitors and their customers in cross-collaborative efforts

Virtual testing is a method that simulates lab testing using multi-body dynamic analysis software. The main advantages of this approach include that the design can be evaluated before a prototype is available and virtual testing results can be easily validated by subsequent physical testing. The disadvantage is that accurate specimen models are sometimes hard to obtain since nonlinear components such as tires, bushings, dampers, and engine mounts are hard to model. Therefore, virtual testing accuracy varies significantly. The typical virtual rigs include tire and spindle coupled test rigs for full vehicle tests and multi-axis shaker tables for component tests. Hybrid simulation combines physical and virtual components, inputs and constraints to create a composite simulation system. Hybrid simulation enables the hard to model components to be tested in the lab.

One of the most important challenges for electronic stability control (ESC) systems is the identification and monitoring of tire rolling environment, especially actual tire-road friction parameters. The presented research considers an advanced variant of the ESC system deducing the mentioned factors based on intelligent methods as fuzzy sets. The paper includes: Overview of key issues in prototyping the algorithms of Electronic Stability Control. Case study for vehicle model. Procedures for monitoring of tire rolling environment: theoretical backgrounds, computing methods, fuzzy input and output variables, fuzzy inference systems, interface with ESC algorithm. Case study for ESC control algorithm. Examples of simulation using Hardware-in-the-Loop procedures. The proposed approach can be widely used for the next-generation of ESC devices having the close integration with Intelligent Transport Systems.

In order to address the CO₂ emissions issue and to diversify the energy for transportation, CNG (Compressed Natural Gas) is considered as one of the most promising alternative fuels given its high octane number. However, gaseous injection decreases volumetric efficiency, impacting directly the maximal torque through a reduction of the cylinder fill-up. To overcome this drawback, both independent natural gas and gasoline indirect injection systems with dedicated engine control were fitted on a RENAULT 2.0L turbocharged SI (Spark Ignition) engine and were adapted for simultaneous operation. The main objective of this innovative combination of gas and liquid fuel injections is to increase the volumetric efficiency without losing the high knocking resistance of methane.

The application of stability systems on heavy vehicles clearly has numerous advantages, when the cost of the cargo, the service life of vehicles, and the vehicle potential for damage are taken into account. The primary objective of such systems is to assist the driver to maintain control in the face of uncertain driving conditions. The dynamic effects of such system, however, are not widely tested by the industry. The study presented in this paper will present an evaluation of the effects of full and partial stability systems on tractor-trailers using hardware-in-the-loop simulation. With the advancement of simulation capabilities that enables the repeatability of maneuvers, the study presented attempts to provide various deterministic “what-if” scenarios under various vehicle stability system combinations.

This work describes the development and use of the Hardware-in-the-Loop (HIL) technique to evaluate the dynamic behavior of a torsional vibration rubber damper (TVD) used in a spark ignition internal combustion engine. The TVD was adapted to a test bench designed for this research and the HIL technique was applied considering the simulated dynamic response of the crankshaft. The results of the torsional vibration amplitudes are compared with measured values in a steady-state well identified condition, to experimentally validate the proposed mathematical model and the possibility to use the HIL technique to evaluate dampers and crankshaft behavior in realistic long term tests, where the rubber degradation also affects the dynamic response of the system. Finally, it was concluded that simulated and measured signals presented a good correlation in some engine operational conditions, reaching the objectives of this study.

The adoption of the electronic controlled steering systems with new technologies has been extended in recent years. They have interactions with other complex vehicle subsystems and it is a hard task for the vehicle developer to find the best solution from huge number of the combination of parameter settings with track tests. In order to improve the efficiency of the steering system development, the authors had developed a steering bench test method for steering system using a Hardware-In-the-Loop Simulation (HILS). In the steering HILS system, vehicle dynamics simulation and the tie rod axial force calculation are required at the same time in the real-time simulation environment. The accuracy of the tie rod axial force calculation is one of the key factors to reproduce the vehicle driving condition. But the calculation cannot be realized by a commercial software for the vehicle dynamics simulation.

This research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

This paper proposes a new integrated chassis control (ICC) using a predictive model-based control (MPC) for optimal allocation of sub-chassis control systems where a predictive model has 6 Degree of Freedom (DoF) for rigid body dynamics. The 6 DoF predictive vehicle model consists of longitudinal, lateral, vertical, roll, pitch, and yaw motions while previous MPC research uses a 3 DoF maximally predictive model such as longitudinal, lateral and yaw motions. The sub-chassis control systems in this paper include four wheel individual braking torque control, four wheel individual driving torque control and four corner active suspension control. Intermediate control inputs for sub-chassis control systems are simplified as wheel slip ratio changes for driving and braking controls and vertical suspension force changes for an active suspension control.