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A truck platooning system was tested using two heavy-duty tractor-trailer trucks on a closed test track to investigate the sensitivity of intentional lateral offsets over a range of intervehicle spacings. The fuel consumption for both trucks in the platoon was measured using the SAE J1321 gravimetric procedure while travelling at 65 mph and loaded to a gross weight of 65,000 lb. In addition, the SAE J1939 instantaneous fuel rate was calibrated against the gravimetric measurements and used as proxy for additional analyses. The testing campaign demonstrated the effects of intervehicle gaps, following-vehicle longitudinal control, and manual lateral control. The new results are compared to previous truck-platooning studies to reinforce the value of the new information and demonstrate similarity to past trends. Fuel savings for the following vehicle was observed to exceed 10% at closer following distances.

Accurate estimation of the State of Charge (SOC), maximum capacity (Qmax) and internal resistance (R0) are essential for efficient battery monitoring, which is an important part of the battery management system. SOC provides information regarding the instantaneous status of the battery system, while Qmax is a key indicator of the long-term State of Health (SOH) of the cell, which represents the abilities of a battery to store energy and retain charge over extended periods. In addition, the internal resistance is also required to predict the peak available power. Traditional methods use complex models and look-up tables that have high computation requirements and are thus unsuitable for online applications. In this paper, we propose a simple method for simultaneous SOC, Qmax and internal resistance estimation based on a second-order equivalent circuit model (ECM).

The existing models and algorithms for predicting human reachable workspaces do not allow users to specify important performer and task parameters, such as body weight and muscular strengths of reach performer and hand-held object's weight. This makes it difficult to consider individuals with unique physical characteristics (e.g., obesity, muscle strength deficiencies and injuries) and many common tasks involving hand-held objects during reach analyses. To address this, this study presents a novel, biomechanically based workspace generation algorithm. Given a set of input data specified in terms of body dimensions, joint ranges of motion, body joints muscular strengths, gender, body weight of a reach performer and a hand-held load weight, the algorithm generates the corresponding reachable workspace. The algorithm combines the existing human figure based modeling approach with empirically obtained biomechanical data and established biomechanical models and constraints.

This paper describes the design and fabrication of a composite body for a solar-electric vehicle. The body shape selected was chosen to optimize the aerodynamics and solar collection features essential to a solar-electric vehicle, and refined using wind-tunnel information from a one-sixth scale model. The computer model was transformed into a full scale model which was then used to produce glass fiber and resin molds capable of withstanding high temperatures. These molds were then used to construct a composite Kevlar/Nomex honeycomb/Kevlar body using a high temperature vacuum bagging technique, in an autoclave at a temperature of 175°C. The details of the construction process are described. Experiments were conducted on samples to test various mechanical properties of the finished product.

A Computational Fluid Dynamics (CFD) study was completed to characterize the fuel consumption in terms of the separation distance of a Driver-Assistive-Truck-Platooning (DATP). The DATP system considered utilizes radar and GPS for a redundant range measurement, paired with Vehicle to Vehicle (V2V) communications to enable regulation of the longitudinal distance between the pair of trucks without acceleration input from the rear driver. The linkage of information between the trucks promotes increased safety between the following trucks, while improving their fuel economy. The results from this study are compared to previous works. Preliminary analysis of the system indicated that the fuel economy of both trucks increases dramatically as the separation distance diminishes. Additionally, an SAE Type-II fuel economy test complying with the (1986) SAE J1321 standard was completed to correlate the computational studies.

A Computational Fluid Dynamics (CFD) study was conducted on four-vehicle platoons, and the aerodynamic data is then coupled with a high-fidelity truck simulation software (TruckSim) to determine fuel efficiency. Previous studies typically have focused on identical two vehicle platoons, whereas this study accounted for more complex platoon configurations. Heavy duty vehicles (HDVs), both military and commercial, make up a significant percentage of fuel consumption. This study aimed to quantify fuel savings of a platoon consisting of dissimilar trucks and trailers, thus reducing vehicle operational cost. The vehicle platoon featured two M915 trucks and two Peterbilt 579 trucks with dissimilar trailer configurations. An unloaded flatbed trailer, a centered 20 ft shipping container, two 20 ft shipping containers, and a 53 ft box trailer configurations were utilized.

Selection of springs and dampers is one of the most important considerations when finalizing a race car suspension design. It is also one of most complex due to the dynamic interaction of the vehicle with the ground. Current tuning methods for spring and dampers' effect on vehicle ride can be based on simplified dynamic models of the vehicle, such as the quarter-car model. While efficient computationally, the traditional quarter-car model does not account for the non-linear variation in grip seen by a fluctuating contact-patch. Both amplitude and frequency of suspension oscillation contribute to loss of tire grip. The method can be improved by incorporation of a dynamic tire model, though resulting in non-linear effects. An improved ‘rolling quarter-car’ model is created, which includes the effect of dynamic tire forces in the analysis of improved grip. Using typical Formula SAE race car, characteristics as a test case, a linearized dynamic model is made.

At 70 miles per hour, overcoming aerodynamic drag represents about 65% of the total energy expenditure for a typical heavy truck vehicle. The goal of this US Department of Energy supported consortium is to establish a clear understanding of the drag producing flow phenomena. This is being accomplished through joint experiments and computations, leading to the intelligent design of drag reducing devices. This paper will describe our objective and approach, provide an overview of our efforts and accomplishments related to drag reduction devices, and offer a brief discussion of our future direction.

Even with relatively unrestrictive rules in the Formula SAE competition, established teams are fighting diminishing returns in vehicle mass and engine horsepower. The typical FSAE vehicle incorporates a six speed gearbox, yet reaches a (course-limited) top speed in competition of only about 110 kph. Selecting a final drive for this top speed would result in 5 gearshifts in less than 4 seconds. As a result, final drive ratio is very sensitive to shift delay time. Although vehicle mass, engine performance and traction still play a major role, a typical FSAE vehicle acceleration is significantly limited by the time it takes to complete a gearshift.

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces greenhouse gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel.

Many lightweight vehicles use non-ventilated (also called vane-less or solid) iron alloy rotors in their vehicle braking systems both on the front and rear wheels. This solid rotor configuration is also common on the rear wheels of many full size production vehicles. This paper's object is to identify the heat transfer coefficients of such a solid brake disc arrangement using different experimental methods and then show how this information can be used both as a design tool and a simulator to predict temperatures in unknown or untested conditions.

Platooning heavy-duty trucks decreases aerodynamic drag for following trucks, reducing energy consumption, and increasing both range and mileage. Previous platooning experimentation has demonstrated fuel economy benefits in two-, three-, and four-truck configurations. However, exogenous variables disturb the ability of these platoons to maintain the desired formation, causing an accordion effect within the platoon and reducing energy benefits via acceleration/deceleration events. This phenomenon is increasingly exacerbated as platoon size and road grade variations increase. The current work assesses how platoon size, road curvature, and road grade influence platoon energy efficiency. Fuel consumption rate is experimentally quantified for four heterogeneous Class 8 vehicles operating in standalone (baseline), two-, and four-truck platooning configurations to assess fuel consumption changes while driving through diverse road conditions.

This paper will describe the development of a load estimation algorithm that is used to estimate the load parameters necessary to detect a vehicle’s proximity to rollover. When operating a vehicle near its handling limits or with large loads, vehicle rollover must be considered for safe operation. Vehicle mass and center of gravity (CG) height play a large role in a vehicle’s rollover propensity. Cargo and passenger vehicles operate under a range of load configurations; therefore, changes in load should be estimated. Researchers have often developed load estimation and rollover detection algorithms separately. This paper will develop a load estimation algorithm and use the load estimates and vehicle states to detect rollover. The load estimation algorithm uses total least squares and is broken into two parts. First, mass is estimated based on a “full-car” dynamic ride model. Next, the CG height and inertia are estimated using the previously estimated mass and a dynamic roll model.

This paper describes a configuration and controller, designed using Autonomie,1 for dual-motor battery electric vehicle (BEV) heavy-duty trucks. Based on the literature and current market research, this model was designed with two electric motors, one on the front axle and the other on the rear axle. A rule-based control algorithm was designed for the new dual-motor BEV, based on the model, and the control parameters were optimized by using a genetic algorithm (GA). The model was simulated in diverse driving cycles and gradeability tests. The results show both a good following of the desired cycle and achievement of truck gradeability performance requirements. The simulation results were compared with those of a single-motor BEV and showed reduced energy consumption with the high-efficiency operation of the two motors.

Platooning vehicles present novel pathways to saving fuel during transportation. With the rise of autonomous solutions, platooning becomes an increasingly apparent sector requiring the application of this new technology. Platooning vehicles travel together intending to reduce aerodynamic resistance during operation. Drafting allows following vehicles to increase fuel economy and save money on refueling, whether that be at the pump or at a charging station. However, autonomous solutions are still in infancy, and controller evaluation is an exciting challenge proposed to researchers. This work brings forth a new application of an emissions quantification metric called vehicle-specific power (VSP). Rather than utilize its emissions investigative benefits, the present work applies VSP to heterogeneous Class 8 Heavy-Duty truck platoons as a means of evaluating the efficacy of Cooperative Adaptive Cruise Control (CACC).

Platooning is a promising technology which can mitigate greenhouse gas impacts and reduce transportation energy consumption. Platooning is a coordinated driving strategy where trucks align themselves in order to realize aerodynamic benefits to reduce required motive force. The aerodynamic benefit is seen as either a “pull” effect experienced by the following vehicles or a “push” effect experienced by the leader. The energy savings magnitude increases nonlinearly as headway (following distance) is reduced [1]. In efforts to maximize energy savings, cooperative adaptive cruise control (CACC) is utilized to maintain relatively short headways. However, when platooning is attempted in the real world, small transient accelerations caused by imperfect control result in observed energy savings being less than expected values. This study analyzes the performance of a recently developed nonlinear model predictive control (NMPC) platooning strategy over challenging terrain.

Due to aerodynamic drag reduction, vehicles may have significant energy savings while platooning in close succession. However, when circumstances force active deceleration to maintain the platoon, such as during vehicle cut-ins or grade changes, the aerodynamic efficiency benefits may be undermined by losses in kinetic energy. In this work, a theoretical relationship is derived to correlate the amount of active deceleration a vehicle experiences with energy efficiency. The derived relationship is leveraged to analyze platooning data from the last vehicle in a class 8 vehicle platoon. The data include both two- and four-truck platoons operating under nine different truck-to-truck gap control strategies. Using J1939 CAN data and GPS-estimated grade profiles, off-throttle data were isolated and longitudinal acceleration is estimated as a function of grade using Kalman filtering.

AC impedance measurements have been taken for five different double-layer capacitors (DLCs) operating at different DC bias levels. Using these measurements, circuit parameters for different DLC equivalent circuits have been determined. The effect of DC bias on the circuit parameters has been investigated. Variations in manufacturing were also examined. Equivalent circuit parameters were calculated for a small group of 50F DLCs and then compared. The equivalent circuit parameters varied about 10% over the sample set.

An experimental technique has been developed to measure the local velocity in molten metals. Couette flow of liquid aluminum, lead, tin and low melting alloy in cylindrical container was chosen for calibration of the experimental technique and the magnetic probe. Velocity and temperature profiles for liquid aluminum rotating in cylindrical container at different angular velocities are obtained for two different values of the depth. We determined that the velocity values increase with magnetic induction, and the relationship between the normalized azimuthal velocity and the magnetic induction can be expressed by quadratic function.

Thermal barrier coatings with low conductivity and low heat capacity have been shown to improve the performance of homogeneous charge compression ignition (HCCI) engines. These coatings improve the combustion process by reducing heat transfer during the hot portion of the engine cycle without the penalty thicker coatings typically have on volumetric efficiency. Computational fluid dynamic simulations with conjugate heat transfer between the in-cylinder fluid and solid piston of a single cylinder HCCI engine with exhaust valve rebreathing are carried out to further understand the impacts of these coatings on the combustion process. For the HCCI engine studied with exhaust valve rebreathing, it is shown that simulations needed to be run for multiple engine cycles for the results to converge given how sensitive the rebreathing process is to the residual gas state.