Improving the predictiveness of the quasi-d combustion model for spark ignition engines with flexible intake systems

Fast and predictive simulation tools are prerequisites for pursuing simulation based engine control development. A particularly attractive tradeoff between speed and fidelity is achieved with a co-simulation approach that marries a commercial gas dynamic code WAVE™ with an in-house quasi-dimensional combustion model. Gas dynamics are critical for predicting the effect of wave action in intake and exhaust systems, while the quasi-D turbulent flame entrainment model provides sensitivity to variations of composition and turbulence in the cylinder. This paper proposes a calibration procedure for such a tool that maximizes its range of validity and therefore achieves a fully predictive combustion model for the analysis of a high degree of freedom (HDOF) engines. Inclusion of a charge motion control device in the intake runner presented a particular challenge, since anything altering the flow upstream of the intake valve remains “invisible” to the zero-D turbulence model applied to the cylinder control volume. The solution is based on the use of turbulence multiplier and scheduling of its value. Consequently, proposed calibration procedure considers two scalar variables (dissipation constant C _β and turbulence multiplier C _M ), and the refinements of flame front area maps to capture details of the spark-plug design, i.e. the actual distance between the spark and the surface of the cylinder head. The procedure is demonstrated using an SI engine system with dual-independent cam phasing and charge motion control valves (CMCV) in the intake runner. A limited number of iterations led to convergence, thanks to a small number of adjustable constants. After calibrating constants at the reference operating point, the predictions are validated for a range of engine speeds, loads and residual fractions.     

Multimodal,multiclass stochastic dynamic traffic assignment for evaluating information provision strategies

A multimodal, multiclass stochastic dynamic traffic assignment model was developed to evaluate pre‐trip and enroute travel information provision strategies. Three different information strategies were examined: user optimum [UO], system optimum [SO] and mixed optimum [MO]. These information provision strategies were analyzed based on the levels of traffic congestion and market penetration rate for the information equipment. Only two modes, bus and car, were used for evaluating and calculating the modal split ratio. Several scenarios were analyzed using day‐to‐day and within day dynamic models. From the results analyzed, it was found that when a traffic manager provides information for drivers using the UO strategy and drivers follow the provided information absolutely, the total travel time may increases over the case with no information. Such worsening occurs when drivers switch their routes and face traffic congestion on the alternative route. This phenomenon is the 'Braess Paradox'.     

Perturbation/correlation based optimal internal combustion engine tuning

This paper addresses the application of the perturbation/correlation method to optimizing the torque output of internal combustion engines. This application was inspired by observations of the limitations in current techniques of the automotive performance tuning industry. Performance issues such as errors from true optimum spark timing and fuel injector pulse width values as well as convergence were considered for optimal tuning. The ability of the system to deal with engine cycle-to-cycle variations and their effect on input parameters is also analyzed.     

Fuzzy-logic-based incident detection for signalized diamond interchanges

This paper documents a fuzzy-logic-based incident detection algorithm for signalized urban diamond interchanges. The model is capable of detecting lane-blocking incidents whose effects are manifested by patterns of deterioration in traffic conditions that require adjustments in signal control strategies. As a component of a real-time traffic adaptive control system for signalized diamond interchanges, the algorithm feeds an incident report (i.e., the time, location, and severity of the incident) to the system's optimization manager, which uses that information to determine the appropriate signal control strategy.The performance of the model was studied using a simulation of an actual diamond interchange. The simulation study evaluated the model's performance in terms of detection rate, false alarm rate, and mean time to detect. The model's performance was encouraging, and the fuzzy-logic-based approach is considered promising.     

Development of a semi-empirical friction model in automotive driveshaft joints

High speed and sport utility vehicles with large joint articulation angle demand lower friction in automotive driveshaft joints to meet noise and vibration comfort levels. Thus a more thorough understanding of internal friction characteristics and mechanisms is required. In this paper, a friction model in automotive driveshaft joints was developed through the use of test data from an instrumented Constant Velocity (CV) joint friction apparatus with actual driveshaft assemblies. Experiments were conducted under different realistic operating conditions of oscillatory speeds, CV joint articulation angles, lubrication, and torque. The experimental data was used to develop a physics-based semi-empirical CV joint internal friction model as a function of different CV joint operating parameters. It was found that the proposed friction model captures the experimental results well. Also the friction model estimates the generated axial force (GAF) in tripod CV joints well, which is the main source of force that causes vehicle vibration problems.     

Development of a low-noise cooling fan for an alternator using numerical and doe methods

An alternator, which converts mechanical rotational energy into electrical energy, is an important component of a vehicle. Alternators operate over a broad range of rotational speeds, typically from 3,000 RPM to 18,000 RPM, which demands a cooling fan producing sufficient airflow, ideally with a minimum of noise. In the current study, an optimized alternator-cooling fan was developed through a linked DOE(Design OF Experiment) process and numerical analysis. The SC/Tetra and FlowNoise S/W programs were used to calculate flow rates and noise levels, respectively, for the newly developed fan. Compared with original model, the numerical results predicted a 3 dBA noise reduction; the measured reduction was 4 dBA.     

Development of a navigation algorithm with dead reckoning for unmanned ground vehicles

A navigation algorithm is indispensable for Unmanned Ground Vehicles (UGVs). During driving, UGVs follow a global path. In this study, we propose a navigation algorithm using Real Time Kinematic (RTK)-Differential Global Positioning System (DGPS) units and encoders to complement global path planning. Sometimes GPS systems lose their signals and receive inaccurate position data due to many factors, such as edifice and barrier obstructions. This paper shows that GPS deviations can be solved using a Dead Reckoning (DR) navigation method with encoders and that position errors can be decreased through the use of RTK-DGPS units. In addition to this method, we will introduce a new waypoint update algorithm and a steering algorithm using RTK-DGPS units.     

Modified lateral control of an autonomous vehicle by look-ahead and look-down sensing

This paper presents a modified lateral control method for an autonomous vehicle with both look-ahead and look-down sensing systems. To cope with sensor noise and modeling uncertainty in the lateral control of the vehicle, a modified LMI-based H lateral controller was proposed, which uses the look-ahead information of the lateral offset error measured at the front of vehicle and the look-down information of the vehicle yaw angle error between the reference lane and the centerline of the vehicle. To verify the safety and the performance of the lateral control, a scaled-down vehicle was developed, and the positioning of the vehicle was estimated with USAT. The proposed controller, which uses both look-ahead and look-down information, was tested for lane changing and reference lane tracking with both simulation and experiment. The simulation and experimental results show that the proposed controller has better tracking and handling performance compared with a controller that uses only the look-ahead information of the target heading angle error.     

Design framework for FlexRay network parameter optimization

Because the FlexRay protocol has more than 70 configuration parameters and these parameters correlate with each other, designing a FlexRay network is a complex and difficult task. In this study, we propose a design framework that optimizes the two main FlexRay network parameters that are highly relevant to the application algorithm. The design process is composed of two steps for optimizing parameters. In the first step, the static slot length is optimized using a frame-packing algorithm. This algorithm binds network signals into static frames based on their periods and signal groups. In the second step, the communication cycle length is optimally designed with frame-scheduling algorithm and worst-case reponse time analysis. Based on the frame-scheduling algorithm, the response times are analyzed. The proposed design framework was applied to a unified chassis control system as a case study, and the analytical results were verified.