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The use of a hydraulic drive system with accumulator energy storage has the potential of providing large gains in fuel economy of internal combustion engine passenger automobiles. The improvement occurs because of efficient regenerative braking and the practicality of decoupling the engine operation from the driving cycle demands. The concept under study uses an engine-driven pump supplying hydraulic power to individual wheel pump/motors (P/M's) and/or an accumulator. Available P/M's have high efficiencies (e.g., 95%) at the ideal point of operation, but the efficiency falls off considerably at combinations of pressure, speed, and displacement that are significantly away from ideal. In order to maximize the fuel economy of the automobile, it is necessary to provide the proper combination of components, system design, and control policies that operate the wheel P/M's as close as possible to their maximum efficiency under all types of driving and braking conditions.

The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

Smaller locomotives often use mechanical transmissions instead of diesel-electric drive systems typically used in larger locomotives. This paper discusses how Model Based Design was used to develop the complete drive train control system for a 24 ton sugar cane locomotive. A complete MATLAB Simulink machine model was built to fully test and verify the shift control logic, traction control, vehicle speed limiting, and braking control for this locomotive application before it was commissioned. The model included the engine, torque converter, planetary transmission, drive line, and steel on steel driving surface. Simulation was used to debug all control code and test and refine control strategies so that the initial field commissioning in remote Australia was executed very quickly with minimal engineering support required.

Using a low-speed high-torque (LSHT) pump/motor to provide the speed range and torque for a hydrostatic automobile offers a number of advantages over using a high-speed low-torque pump/motor, combined with a gear reducer. However, there appear to be no LSHT units commercially available that have true variable displacement capability. Because of this void, a variable displacement pump/motor has been designed and built that could provide a direct drive for each wheel of a hydrostatic automobile. The unit uses some components such as the cylinder block, piston and modified rotating case from a commercially available radial piston pump/motor. Initial preliminary testing of the pump/motor indicates that it has good efficiency and performance characteristics, and, with further development should be very attractive for automotive use. This paper focuses on the design and kinematics of the device.

NVH is gaining importance in the quality perception of off-highway machine performance and operator comfort. Booming noise, a low frequency NVH phenomenon, can be a significant sound issue in an off-highway machine. In order to increase operator comfort by decreasing the noise levels and noise annoyance, a tuned mass damper (TMD) was added to the resonating panel to suppress the booming. Operational deflection shapes (ODS) and experimental modal analysis (EMA) were performed to identify the resonating panels, a damper was tuned in the lab and on the machine to the specific frequency, machine operational tests were carried out to verify the effectiveness of the damper to deal with booming noise.

Brake systems in current production automobiles are the result of a long evolutionary process beginning with the first practical hydraulic brake patent in 1917. While the basic hydraulic design has many advantages, recent modifications to this system for anti-lock braking and traction control considerably increase the cost of manufacture. As a result, many manufacturers are investigating the possibility of developing alternate braking system structures that cost less and can easily interface with vehicle electronics. Evaluating these systems for fault tolerance and failure effects is crucial to provide a safe and reliable vehicle braking system. This paper demonstrates the use of the Fault Tree Analysis method for carrying out such an evaluation. An example system is presented to illustrate the application of this method to automobile brake design.

Traffic state identification is a key problem in intelligent transportation system. As a new technology, connected and automated vehicle can play a role of identifying traffic state with the installation of onboard sensors. However, research of lane level traffic state identification is relatively lacked. Identifying lane level traffic state is helpful to lane selection in the process of driving and trajectory planning. In addition, traffic state identification precision with low penetration of connected and automated vehicles is relatively low. To fill this gap, this paper proposes a novel method of identifying traffic state in the presence of connected and automated vehicles with low penetration rate. Assuming connected and automated vehicles can obtain information of surrounding vehicles’, we use the perceptible information to estimate imperceptible information, then traffic state of road section can be inferred.

Identifying edge cases for designed algorithms is critical for functional safety in autonomous driving deployment. In order to find the feasible boundary of designed algorithms, simulations are heavily used. However, simulations for autonomous driving validation are expensive due to the requirement of visual rendering, physical simulation, and AI agents. In this case, common sampling techniques, such as Monte Carlo Sampling, become computationally expensive due to their sample inefficiency. To improve sample efficiency and minimize the number of simulations, we propose a tailored active learning approach combining the Support Vector Machine (SVM) and the Gaussian Process Regressor (GPR). The SVM learns the feasible boundary iteratively with a new sampling point via active learning. Active Learning is achieved by using the information of the decision boundary of the current SVM and the uncertainty metric calculated by the GPR.

Brake pulsation is a low frequency vibration phenomenon in brake judder. In this study, a simulation approach has been developed to understand the physics behind brake pulsation employing a full vehicle dynamics CAE model. The full vehicle dynamic model was further studied to understand the impact of suspension tuning variation to brake pulsation performance. Brake torque variation (BTV) due to brake thickness variation from uneven rotor wear was represented mathematically in a sinusoidal form. The wheel assembly vibration from the brake torque variation is transmitted to driver interface points such as the seat track and the steering wheel. The steering wheel lateral acceleration at the 12 o’clock position, driver seat acceleration, and spindle fore-aft acceleration were reviewed to explore the physics of brake pulsation. It was found that the phase angle between the left and right brake torque generated a huge variation in brake pulsation performance.