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Journal Article

Toward Improving Vehicle Fuel Economy with ADAS

Abstract Modern vehicles have incorporated numerous safety-focused advanced driver-assistance systems (ADAS) in the last decade including smart cruise control and object avoidance. In this article, we aim to go beyond using ADAS for safety and propose to use ADAS technology to enable predictive optimal energy management and improve vehicle fuel economy (FE). We combine ADAS sensor data with a previously developed prediction model, dynamic programming (DP) optimal energy management control, and a validated model of a 2010 Toyota Prius to explore FE. First, a unique ADAS detection scope is defined based on optimal vehicle control prediction aspects demonstrated to be relevant from the literature. Next, during real-world city and highway drive cycles in Denver, Colorado, a camera is used to record video footage of the vehicle environment and define ADAS detection ground truth. Then, various ADAS algorithms are combined, modified, and compared to the ground truth results.
Journal Article

Thermohydrodynamic Modeling of Squeeze Film Dampers in High-Speed Turbomachinery

Abstract This work develops a comprehensive thermohydrodynamic (THD) model for high-speed squeeze film dampers (SFDs) in the presence of lubricant inertia effects. Firstly, the generalized expression for Reynolds equation is developed. Additionally, in order to reduce the complexity of the hydrodynamic equations, an average radial viscosity is defined and integrated into the equations. Subsequently, an inertial correction to the pressure is incorporated by using a first-order perturbation technique to represent the effect of lubricant inertia on the hydrodynamic pressure distribution. Furthermore, a thermal model, including the energy equation, the Laplace heat conduction equations in the surrounding solids (i.e. the journal and the bush), and the thermal boundary conditions at the interfaces is constructed. Moreover, the system of partial differential hydrodynamic and thermal equations is simultaneously solved by using an iterative numerical algorithm.
Journal Article

Evaluating How Functional Performance in Aerospace Components Is Affected by Geometric Variation

Abstract Geometric variation stemming from manufacturing can be a limiting factor for the quality and reliability of products. Therefore, manufacturing assessments are increasingly being performed during the early stages of product development. In the aerospace industry, products are complex engineering systems, the development of which require multidisciplinary expertise. In such contexts, there are significant barriers against assessing the effects of geometric variation on the functionality of products. To overcome these barriers, this article introduces a new methodology consisting of a modelling approach linked to a multidisciplinary simulation environment. The modelling approach is based on the parametric point method, which allows point-scanned data to be transferred to parameterised CAD models. In a case study, the methodology is implemented in an industrial setting.
Journal Article

Hydro-Pneumatic Energy Harvesting Suspension System Using a PSO Based PID Controller

Abstract In this article, a unique design for Hydro-Pneumatic Energy Harvesting Suspension HPEHS system is introduced. The design includes a hydraulic rectifier to maintain one-way flow direction in order to obtain maximum power generation from the vertical oscillation of the suspension system and achieve handling and comfort car drive. A mathematical model is presented to study the system dynamics and non-linear effects for HPEHS system. A simulation model is created by using Advanced Modeling Environment Simulations software (AMEsim) to analyze system performance. Furthermore, a co-simulation platform model is developed using Matlab-Simulink and AMEsim to optimize the PID controller parameters of the external variable load resistor applied on the generator by using Particle Swarm Optimization (PSO).
Journal Article

Optimal Electric Vehicle Design Tool Using Genetic Algorithms

Abstract The proposed approach present the development of a computer tool that allows, in the first phase, the modeling of the electric vehicle power chain. This phase is based on a library developed under the Matlab-Simulink simulation environment. This library contains all the components of the power chain; it offers the selection of the desired configuration of each component. In the second phase, the tool solves the autonomy optimization problem. This problem is resolved by a program based on genetic algorithms. This program permits to optimize the configuration parameters maximizing the vehicle autonomy of the chosen chain. This tool is based on a graphical interface developed under the Matlab simulation environment.
Journal Article

Automated ASIL Allocation and Decomposition according to ISO 26262, Using the Example of Vehicle Electrical Systems for Automated Driving

Abstract ISO 26262 needs to be considered when developing safety-relevant E/E systems within the automotive industry. One part of the development process according to ISO 26262 is the derivation of the safety requirements for component functions. Here, one attribute of the safety requirements is the Automotive Safety Integrity Level (ASIL). The ASIL at a component level can be determined using ASIL allocation and decomposition. Considering complex systems such as vehicle electrical systems, countless possibilities can be identified for how the ASILs at a component level can be assigned in line with safety goals. In terms of efficiency, manual assignment is not expedient. Therefore, an algorithm for automated assignment of the ASILs will be introduced which considers constraints based on a fault tree analysis. The function of the approach will be demonstrated using the example of a vehicle electrical system from an automated vehicle.
Journal Article

Investigation of a Six-Phase Interior Permanent Magnet Synchronous Machine for Integrated Charging and Propulsion in EVs

Abstract Merits such as reduced weight, overall and operational costs of the electric vehicle (EV) while providing level 3 charging capability, are propelling research on integrated charging (IC) technology for EVs. Since the same interior permanent magnet synchronous machine (IPMSM) is used during IC and traction conditions, it is important to understand the behavior of the machine during these conditions and optimally design the machine. Hence, firstly, this paper presents a case study on performance of a laboratory 3-phase IPMSM under IC and traction conditions. Thereafter, understanding the challenges such as low magnet operating point, losses and torque oscillation in 3-phase IPMSM during IC, a 6-phase IPMSM with an unconventional configuration is investigated to yield traction characteristics like that of the 3-phase IPMSM and mitigate challenges during IC. In the process, mathematical model of the 6-phase IPMSM is developed employing the dq-axis theory.
Journal Article

Railway Fastener Positioning Method Based on Improved Census Transform

Abstract In view of the fact that the current positioning methods of railway fasteners are easily affected by illumination intensity, bright spots, and shadows, a positioning method with relative grayscale invariance is proposed. The median filter is used to remove the noise in order to reduce the adverse effects on the subsequent processing results, and the baffle seat edge features are enhanced by improved Census transform. The mean-shift clustering algorithm is used to classify the edges to weaken the interference by short lines. Finally, the Hough transform is used to quickly extract the linear feature of the baffle seat edge and achieve the exact position of the fastener with the prior knowledge. Experimental results show that the proposed method can accurately locate and have good adaptability under different illumination conditions, and the position accuracy is increased by 4.3% and 8%, respectively, in sunny and rainy days.
Journal Article

In-Plane Flexible Ring Tire Model Parameter Identification: Optimization Algorithms

Abstract Parameter identification is an important part of tire model development. The prediction performance of a tire model highly depends on the identified parameter values of the tire model. Different optimization algorithms may yield different tire parameters with different computational accuracy. It is essential to find out which optimization algorithm is most likely to generate a set of parameters with the best prediction performance. In this study, four different MATLAB® optimization algorithms, including fminsearchcon, patternsearch, genetic algorithm (GA), and particleswarm, are used to identify the parameters of a newly proposed in-plane flexible ring tire model. The reference data used for parameter identification are obtained through a ADAMS FTire® virtual cleat test. After parameters are identified based on above four algorithms, their performances are compared in terms of effectiveness, efficiency, reliability, and robustness.
Journal Article

Active Suspension: Future Lessons from The Past

Abstract Active suspension was a topic of great research interest near the end of last century. Ultimately broad bandwidth active systems were found to be too expensive in terms of both energy and financial cost. This past work, developing the ultimate vehicle suspension, has relevance for today’s vehicle designers working on more efficient and effective suspension systems for practical vehicles. From a control theorist’s perspective, it provides an interesting case study in the use of “practical” knowledge to allow “better” performance than predicted by theoretically optimal linear controllers. A brief history of active suspension will be introduced. Peter Wright, David Williams, and others at Lotus developed their Lotus modal control concept. In a parallel effort, Dean Karnopp presented the notion of inertial (Skyhook) damping. These concepts will be compared, the combination of these two distinctly different efforts will be discussed, and eventual vehicle results presented.
Journal Article

Optimization Control for 4WIS Electric Vehicle Based on the Coincidence Degree of Wheel Steering Centers

Abstract The steering centers of four wheels for passenger car do not coincide, which may result in tire wear and the unharmoniously movement of the vehicle. In this article, an optimization control method for Four Wheel Independent Steering (4WIS) electric vehicle based on the coincidence degree of steering centers is proposed, to improve the driving performance. The nonlinear vehicle model of the four-wheel independent steering vehicle is established, and the formula of the wheel steering center is derived. The coincidence degree of wheel steering centers is defined as the evaluation index, to describe and evaluate the performance of the coordination for wheels’ movement. Meanwhile, the structure design of 4WIS system and the establishment of Direct-Current (DC) steering motor model are carried out, and the Model Predictive Control (MPC) controller for steering actuator is designed.
Journal Article

Influence of Intelligent Active Suspension System Controller Design Techniques on Vehicle Braking Characteristics

Abstract This article presents a comprehensive investigation for the interaction between vehicle ride vibration control and braking control using two degrees of freedom (2DOF) quarter vehicle model. A typical limited bandwidth active suspension system with nonlinear spring and damping characteristics of practical hydraulic and pneumatic components is controlled to regulate both suspension and tire forces and therefore provide the optimum ride comfort and braking performance of an anti-lock brake system (ABS). In order to design a suitable controller for this nonlinear integrated system, various control techniques are followed including state feedback tuned using Linear Quadratic Regulator (LQR), state feedback tuned using Genetic Algorithm (GA), Proportional Integrated (PI) tuned genetically, and Fuzzy Logic Control (FLC). The ABS control system is designed to limit skid ratio below threshold of 15%.
Journal Article

Development, Testing, and Assessment of a Kinematic Path-Following Model for Towing Vehicle Systems

Abstract A kinematic path-following model is developed based on an existing modeling framework established by the authors [1, 2] for prediction of the paths of towing vehicle systems. The presented path-following model determines the path of the towing vehicle using the vehicle’s speed and acceleration data collected by an inertial measurement unit (IMU). An Ackerman steering model was presented to calculate instantaneous directional angles and radii for each towed vehicle based on its geometric data and steering angle. In that model the off-tracking effect is properly captured. A 1:4 scale model for a towing vehicle system was built to test the developed steering model, and it was found that the angles and radii of the towing vehicle and each towed unit calculated using the Ackerman steering model agreed very well with those measured from the scale model.
Journal Article

Design and Implementation of a Hybrid Fuzzy-Reinforcement Learning Algorithm for Driver Drowsiness Detection Using a Driving Simulator

Abstract Driver drowsiness is the cause of many fatal accidents all over the world. Many research works have been conducted on detecting driver drowsiness for more than half a century, but statistical data show that such accidents have not decreased significantly. Most researchers have focused on using certain sensors and extracting their relevant features. However, there has been no research work on developing an algorithm to detect driver drowsiness independently from the input type. In this paper, a hybrid fuzzy-reinforcement learning drowsiness detection algorithm is presented. This algorithm is flexible to work with any number and any kind of data related to driver alertness. It estimates the level of alertness based on an arbitrary number of inputs. The algorithm extracts driving patterns specific to each driver and determines driver’s level of drowsiness using a continuous numerical variable rather than a discrete variable.
Journal Article

Integrated Positioning Method for Intelligent Vehicle Based on GPS and UWB

Abstract Knowledge of intelligent vehicle absolute position is a vital premise for the implementation of decision programming, kinematic and dynamics control. In order to achieve high accuracy positioning and reduce running cost as much as possible under all operating conditions, this paper proposed an integrated positioning method based on GPS and Ultra Wide Band(UWB) for intelligent vehicle’s navigation and position system. In this method, GPS and UWB are alternately active according to the confidence level of GPS signal. When the vehicle is traveling in a wide-open area and GPS signal is well received, the positioning results of Dead Reckoning system are corrected by the low frequency positioning output from GPS. During the correcting process, in order to realize the better fusion of measurement data, a simplified federal Kalman filter was designed by using indirect method.
Journal Article

Efficient Lane Detection Using Deep Lane Feature Extraction Method

Abstract In this paper, an efficient lane detection using deep feature extraction method is proposed to achieve real-time lane detection in diverse road environment. The method contains three main stages: 1) pre-processing, 2) deep lane feature extraction and 3) lane fitting. In pre-processing stage, the inverse perspective mapping (IPM) is used to obtain a bird's eye view of the road image, and then an edge image is generated using the canny operator. In deep lane feature extraction stage, an advanced lane extraction method is proposed. Firstly, line segment detector (LSD) is applied to achieve the fast line segment detection in the IPM image. After that, a proposed adaptive lane clustering algorithm is employed to gather the adjacent line segments generated by the LSD method. Finally, a proposed local gray value maximum cascaded spatial correlation filter (GMSF) algorithm is used to extract the target lane lines among the multiple lines.
Journal Article

2-D CFAR Procedure of Multiple Target Detection for Automotive Radar

Abstract In Advanced Driver Assistant System (ADAS), the automotive radar is used to detect targets or obstacles around the vehicle. The procedure of Constant False Alarm Rate (CFAR) plays an important role in adaptive targets detection in noise or clutter environment. But in practical applications, the noise or clutter power is absolutely unknown and varies over the change of range, time and angle. The well-known cell averaging (CA) CFAR detector has a good detection performance in homogeneous environment but suffers from masking effect in multi-target environment. The ordered statistic (OS) CFAR is more robust in multi-target environment but needs a high computation power. Therefore, in this paper, a new two-dimension CFAR procedure based on a combination of Generalized Order Statistic (GOS) and CA CFAR named GOS-CA CFAR is proposed. Besides, the Linear Frequency Modulation Continuous Wave (LFMCW) radar simulation system is built to produce a series of rapid chirp signals.
Journal Article

Development and Validation Procedure of a 1D Predictive Model for Simulation of a Common Rail Fuel Injection System Controlled with a Fuel Metering Valve

Abstract A fully predictive one-dimensional model of a Common Rail injection apparatus for diesel passenger cars is presented and discussed. The apparatus includes high-pressure pump, high-pressure pipes, injectors, rail and a fuel-metering valve that is used to control the rail pressure level. A methodology for separately assessing the accuracy of the single submodels of the components is developed and proposed. The complete model of the injection system is finally validated by means of a comparison with experimental high-pressure and injected flow-rate time histories. The predictive model is applied to examine the fluid dynamics of the injection system during either steady-state or transient operations. The influence of the pump delivered flow-rate on the rail-pressure time history and on the injection performance is analysed for different energizing times and nominal rail pressure values.
Journal Article

Limitations of Two-Stage Turbocharging at High Flight Altitudes

Abstract High-altitude long-endurance (HALE) unmanned aerial vehicles (UAVs) are used for high flight altitudes, which enable low drag and fast flight with minimal fuel consumption. Two-stage turbocharging is necessary to sustain sea-level power at high flight altitudes. In this study, the limitations of two-stage turbocharging at high flight altitudes typical for HALE UAVs are analyzed for the first time. The obtained results show that the minimum available engine power increases as the altitude rises. This will limit the ability of the aircraft to descend rapidly. Furthermore, at high altitudes, if a lower operating point is required for a fast descent, further recovery to full power for climbing or cruising could be unavailable. In the latter cases, a lower altitude must be reached before full power would be available again. A basic algorithm for the assessment and analysis of the limitations of UAV engines with two-stage turbochargers operating at high altitudes is suggested.
Journal Article

Electrifying Long-Haul Freight—Part II: Assessment of the Battery Capacity

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.