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The number of control actuators available on spark-ignition engines is rapidly increasing to meet demand for improved fuel economy and reduced exhaust emissions. The added complexity greatly complicates control strategy development because there can be a wide range of potential actuator settings at each engine operating condition, and map-based actuator calibration becomes challenging as the number of control degrees of freedom expand significantly. Many engine actuators, such as variable valve actuation and flow control valves, directly influence in-cylinder combustion through changes in gas exchange, mixture preparation, and charge motion. The addition of these types of actuators makes it difficult to predict the influences of individual actuator positioning on in-cylinder combustion without substantial experimental complexity.

A nonlinear eight degree of freedom vehicle model has been used to examine the effects of roll stiffness on handling and performance. In addition, various control strategies have been devised which vary the total roll couple distribution in order to improve cornering capability and stopping distance. Of all cases tested, a controller which varies the total roll stiffness based on roll angle feedback, and continuously updates the roll couple distribution as a function of steering wheel angle, braking input, and the total roll stiffness, yields the greatest improvements in collision avoidance.

Predictable handling of a racecar may be achieved by tailoring chassis stiffness so that roll stiffness between sprung and unsprung masses are due almost entirely to the suspension. In this work, the effects of overall chassis flexibility on roll stiffness and wheel camber response, will be determined using a finite element model (FEM) of a Winston Cup racecar chassis and suspension. The FEM of the chassis/suspension is built from an assembly of beam and shell elements using geometry measured from a typical Winston cup race configuration. Care has been taken to model internal constraints between degrees-of-freedom (DOF) at suspension to chassis connections, e.g. t ball and pin joints and internal releases. To validate the model, the change in wheel loads due to an applied jacking force that rolls the chassis agrees closely with measured data.

A simulation of the vertical response of a nonlinear 1/4 car model consisting of a sprung and an unsprung mass was developed. It is being used for preliminary evaluation of various suspension configurations and control algorithms. Nonlinearities include hysteretic shock damping and switchable damping characteristics. Road inputs include discrete events such as bumps and potholes as well as randomly irregular roads having specified power spectral densities (PSDs). Fast Fourier transform data analysis procedures are used to process data from the simulation to obtain PSDs, rms values, and histograms of various response quantities. To aid in assessing ride comfort, the 1/3 octave band rms acceleration of the sprung mass is calculated and compared with specifications suggested by the International Standards Organization (ISO). Cross plots of the rms values of acceleration, suspension travel, and the force of the road on the tire are used to compare the performance of various suspensions.

Rollover prevention is now part of complete vehicle stability control systems for many vehicles. Given that rollover is predominantly associated with vehicles with high centers of gravity, the targeted vehicles for rollover protection include medium and heavy duty commercial vehicles. Unfortunately, the chassis designs of these vehicles are often so compliant in torsion that the ends of the vehicles may have significantly different roll responses at any given time. The potential need to assess and correct for the roll behavior of the front and rear ends of the vehicle is the subject of this paper. Most rollover mitigation research to date has used rigid chassis assumptions in modeling the vehicle. This paper deals with the roll control of vehicles with torsionally flexible chassis based on a yaw-correction system.

Hydrostatic (hydraulic hybrid) drives have demonstrated energy efficiency and emissions reduction benefits. This paper investigates the potential of an independent hydrostatic wheel drive system for implementing a traction-based vehicle lateral stability control system. The system allows an upper level vehicle stability controller to produce a desired corrective yaw moment via a differential distribution of torque to the independent wheel motors. In cornering maneuvers that require braking on any one wheel of the vehicle, the motors can be operated as pumps for re-generating energy into an on-board accumulator. This approach avoids or reduces activation of the friction brakes, thereby reducing energy waste as heat in the brake pads and offering potential savings in brake maintenance costs. For this study, a model of a 4×4 hydrostatic independent wheel drive system is constructed in a causal and modular fashion and is coupled to a 7 DOF vehicle handling dynamics model.

Three-dimensional simulation has become an indispensable approach to develop improved understanding of ring rolling technology, with validity as the basic requirement of the ring rolling simulation. Cold ring rolling is simple conceptually, however complex to analyze as the metal forming process is subject to coupled effects with multiple influencing factors such as sizes of rolls and ring blank, form geometry, material, process parameters, and frictional effects. Investigating the coupled thermal and plastic deformation behavior (the plastic deformation state and its development) in the deformation zone during the process is significant for predicting metal flow in order to control the geometric and tensile residual stress quality of deformed rings, and to provide for cycle time optimization of the cold ring rolling process.

To facilitate the design of a non-pneumatic tire for NASA's new Moon mission, the authors used the Finite Element Method (FEM) to investigate the interaction between soil and non-pneumatic tire made of different cellular shear bands. Cellular shear bands, made of an aluminum alloy (AL7075-T6), are designed to have the same effective shear modulus of 6.5E+6 Pa, which is the shear modulus of an elastomer. The Lebanon sand of New Hampshire is used in the model. This sand has a complete set of material properties in the literature and Drucker-Prager/Cap plasticity constitutive law with hardening is employed to model the sand. The tires are treated as deformable bodies, and the authors used the penalty contact algorithm to model the tangential behavior of the contact. The friction between tire and sand is considered by using Coulomb's law. Numerical results show deformation of sand and tire.

The use of pulse steering tests for assessment of handling qualities was investigated using a simulation of a comprehensive, nonlinear four wheel model of an automobile. Evaluations were conducted using frequency response functions of yaw rate and lateral acceleration obtained by FFT processing of the simulated response. In addition, as suggested by the work of Mimuro et al [1], four parameters (steady state yaw rate gain, yaw rate natural frequency and damping ratio, and lateral acceleration phase lag at 1 Hz) that characterize these response functions were also obtained by curve fitting techniques. The effects on accuracy of the response functions and the four parameters of variations in pulse shape, duration, and magnitude were investigated. Results from the simulated pulse steer test were compared with those from simulated swept sine steering tests.

The control of body roll on passenger vehicles can be used as a tool for controlling the “weight shift” that occurs during maneuvering. Distribution of load to the tires will determine the ability of each tire to generate lateral forces required for the maneuver and thus will significantly affect handling. In this investigation, the effects on weight shift and hence, on handling, of total roll stiffness, front to rear roll stiffness distribution, total roll damping, and roll damping distribution were examined. These results were then used to guide the development and analysis of several roll control algorithms. The results of the investigation indicate that roll control can be effective in improving handling and stability. However, simulation of the control algorithms showed that the controllers must be specifically tuned for the vehicle in which they are to be used.

The components in a hybrid electric vehicle (HEV) powertrain include the battery pack, an internal combustion engine, and the electric machines such as motors and possibly a generator. These components generate a considerable amount of heat during driving cycles. A robust thermal management system with advanced controller, designed for temperature tracking, is required for vehicle safety and energy efficiency. In this study, a hybridized mid-size truck for military application is investigated. The paper examines the integration of advanced control algorithms to the cooling system featuring an electric-mechanical compressor, coolant pump and radiator fans. Mathematical models are developed to numerically describe the thermal behavior of these powertrain elements. A series of controllers are designed to effectively manage the battery pack, electric motors, and the internal combustion engine temperatures.

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).