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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.

A variety of methodologies to use embedded multicore controllers efficiently has been discussed in the last years. Several assumptions are usually made in the automotive domain, such as static assignment of tasks to the cores. This paper shows an approach for efficient task allocation depending on different system modes. An engine management system (EMS) is used as application example, and the performance improvement compared to static allocation is assessed. The paper is structured as follows: First the control algorithms for the EMS will be classified according to operating modes. The classified algorithms will be allocated to the cores, depending on the operating mode. We identify mode transition points, allowing a reliable switch without neglecting timing requirements. As a next step, it will be shown that a load distribution by mode-dependent task allocation would be better balanced than a static task allocation.

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.

Plug-In Hybrid Vehicles (PHEVs) represent the middle point between Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs), thus combining benefits of the two architectures. PHEVs can achieve very high fuel economy while preserving full functionality of hybrids - long driving range, easy refueling, lower emissions etc. These advantages come at an expense of added complexity in terms of available fuel. The PHEV battery is recharged both though regenerative braking and directly by the grid thus adding extra dimension to the control problem. Along with the minimization of the fuel consumption, the amount of electricity taken from the power grid should be also considered, therefore the electricity generation mix and price become additional parameters that should be included in the cost function.

Generally, the widely used hydraulic control system in automatic transmissions is pulse width modulation (PWM) type. It consists in a PWM solenoid valve and a reducing type second stage valve, so called pressure control valve (PCV), to amplify pressure or flow rate. In this study, the mathematical models of the PWM solenoid valve and the PCV with moderate complexity are proposed. Then, their behavior is analyzed from the steady state characteristics. Finally, we find that there are good matches between the dynamic simulation results and the experimental data.

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 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.

For the improvement of ride quality, development of vibration damping control systems and isolating methods become more important. To define basic ride vibrational modes, the effects of vehicle velocity and wheelbase on the standard road surfaces should be investigated. The different vibrational responses depending on the measurement positions of a vehicle body are presented with the bounce and the pitch motions. A methodology for the isolation of engine mount system's resonance to the road input and periodical excitations of tire/wheel nonuniformity forces are discussed. Using the computer simulation and the experimental results, a useful ride model with respect to the vehicle velocity and the stiffness of engine mount is presented.

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.

As electric vehicles become more widespread, such vehicles may be subject to “range anxiety” due to the risk of discharging during driving or the discharging when left unused for a long period. Accordingly, a vehicle equipped with a mobile charger that can provide a charge in an emergency. The vehicle with the mobile charger is usually composed of a large capacity battery, a power converter in a small truck. However, the large capacity battery and the power converter are disadvantageous in that they are large in size and expensive and should be produced as a special vehicle. In this paper, we propose a method to solve the problem using an internal EV system without requiring an additional power generation, battery and a charging-and-discharging device. The method is a novel Vehicle-to-Vehicle (V2V) fast charging control system utilizing motor and inverter in EV.

The electrical power system is the vital lifeline to most of the control systems on modern vehicles. The demands on the system are highly complex, and a detailed understanding of the system behavior is necessary both to the process of systems integration and to the economic design of a specific control system or actuator. The vehicle electric power system, which consists of two major components: a generator and a battery, has to provide numerous electrical and electronic systems with enough electrical energy. A detailed understanding of the characteristics of the electric power system, electrical load demands, and the driving environment such as road, season, and vehicle weight are required when the capacities of the generator and the battery are to be determined for a vehicle. An easy-to-use and inexpensive simulation program may be needed to avoid the over/under design problem of the electric power system. A vehicle electric power simulator is developed in this study.

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.

This paper proposes a clutch control strategy during in-gear driving situations for Dual Clutch Transmissions (DCTs). The clutch is intentionally controlled to make small amount of a slip to identify the torque transfer capacity. The control objective of this phase is to ensure the clutch slip fairly remaining the specified value. To achieve this, the micro-slip controller is designed based on sliding mode control theory. Experimental verifications performed on onboard control system of the DCT equipped vehicle demonstrate that the proposed controller good tracking performance of the desired slip speed.