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Abstract Truck platooning comprises a number of trucks equipped with automated lateral and longitudinal vehicle control technology, which allows them to move in tight formation with short following distances. This study is an initial step toward developing an understanding of the occupant injury risks associated with the multiple sequential impacts between truck platoons and roadside safety barriers, regardless of whether the crash is associated with a malfunction of automated control or human operation. Full-scale crash impacts of a tractor-trailer platoon into a concrete bridge guardrail were simulated for a specific Test Level condition according to the Manual for Assessing Safety Hardware (MASH) standards. The model of the bridge barrier was developed based on its drawings, and material properties were assigned according to literature data.

Abstract A kinematic modeling framework was established to predict status (position, displacement, velocity, acceleration, and shape) of a towing vehicle system with different driver inputs. This framework consists of three components: (1) a state space model to decide position and velocity for the vehicle system based on Newton’s second law; (2) an angular acceleration transferring model, which leads to a hypothesis that the each towed unit follows the same path as the towing vehicle; and (3) a polygon model to draw instantaneous polygons to envelop the entire system at any time point.

Abstract In this article performance of the innovative Crank-Lever Electromagnetic Damper (CLEMD) for an off-road vehicle suspension system is analyzed. To determine the characteristic behavior of the CLEMD, the damping force it provides on the suspension system is varied by changing the values of the damping coefficient in the simulations. Various parameters considered in the analyses include power regenerated, voltage, current, comfort, road-holding, etc. The behavior of all the parameters of the CLEMD is observed for an off-road vehicle by carrying out simulations on country roads since the off-road vehicles are subjected to higher road irregularities and hence provide an opportunity to regenerate a higher amount of power. A two-dimensional (2-D) model of a vehicle developed in SimMechanics is interfaced with a Simulink model of CLEMDs for the analyses.

Abstract The development, analysis, and optimization of battery electric class-7 heavy-duty trucks equipped with multi-speed transmissions are discussed in this paper. The designs of five new traction motors-fractional-slot, concentrated winding machines-are proposed for use in heavy-duty electric trucks. The procedure for gear-ratio range selection is outlined and ranges of gear ratios for three-to six-speed transmission powertrains are calculated for each of the proposed electric traction motors. The simulation and gear-ratio optimization tasks for class-7 battery electric trucks are formulated. The energy consumption of the e-truck with the twenty possible powertrain combinations is minimized over the four driving cycles and the most efficient powertrain layouts that meet the performance criteria are recommended.

Abstract Aiming to improve the handling performance of heavy tractor semi-trailer during turning or changing lanes at high speed, a hierarchical structure controller is proposed and a hardware-in-the-loop (HIL) test bench of the electronic pneumatic braking system is developed to validate the proposed controller. In the upper controller, a Kalman filter observer based on the heavy tractor semi-trailer dynamic model is used to estimate the yaw rates and sideslip angles of the tractor and trailer. Simultaneously, a sliding mode direct yaw moment controller is developed, which takes the estimated yaw rates and sideslip angles and the reference values calculated by the three-degrees-of-freedom dynamic model of the heavy tractor semi-trailer as the control inputs. In the lower controller, the additional yaw moments of tractor and trailer are transformed into corresponding wheel braking forces according to the current steering characteristics.

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.

Abstract Improving the aerodynamics of heavy trucks is an important consideration in the strive for more energy-efficient vehicles. Cooling drag is one part of the total aerodynamic resistance acting on a vehicle, which arises as a consequence of air flowing through the grille area, the heat exchangers, and the irregular under-hood area. Today cooling packages of heavy trucks are dimensioned for a critical cooling case, typically when the vehicle is driving fully laden, at low speed up a steep hill. However, for long-haul trucks, mostly operating at highway speeds on mostly level roads, it may not be necessary to have all the cooling airflow from an open-grille configuration. It can therefore be desirable for fuel consumption purposes, to shut off the entire cooling airflow, or a portion of it, under certain driving conditions dictated by the cooling demands. In Europe, most trucks operating on the roads are of cab-over-engine type, as a consequence of the length legislations present.

Abstract The effects of exhaust emissions on public welfare have prompted the US Environmental Protection Agency to take various actions toward understanding, modeling, and reducing air pollution from vehicles. This study was performed to better understand exhaust emissions of heavy-duty diesel-powered tractor-trailer trucks that operate in drayage service, which involves the moving of shipping containers to or from port terminals. The study involved the use of portable emissions measurement systems (PEMS) to measure both gaseous and particulate matter (PM) mass emission rates and record various vehicle and engine parameters from the test trucks as they performed their normal drayage service. These measurements were supplemented with port terminal gate entry/exit logs for all drayage trucks entering the two Port of Houston Authority container terminals.

Abstract Commercial vehicles contribute to the majority of freight transportation in the United States. They are also significant fuel consumers, with over 23% of fuel used in transportation in the United States. The gas price volatility and increasingly stringent regulation on greenhouse-gas emissions have driven manufacturers to adopt new fuel-efficient technologies. Among others, an advanced transmission control strategy, which can provide tangible improvement with low incremental cost. In the commercial sector, individual drivers have little or no interest in vehicle fuel economy, contrary to fleet owners. Aggressive driving behavior can greatly increase the real-world vehicle fuel consumption. However, the effectiveness of transmission calibration to match the shift strategy to the driving characteristics is still a challenge.

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.

Abstract This research developed methods for a virtual operator model (VOM) to learn the optimal control inputs for operation of a virtual excavator. Virtual design, used to model, simulate, and test new features, has often been limited by the fidelity of the virtual model of human operators. Human operator learns, over time, the capability, limits, and control characteristics of new vehicles to develop the best strategy to maximize the efficiency of operation. However, VOMs are developed with fixed strategies and for specific vehicle models (VMs) and require time-consuming re-tuning of the VOM for each new vehicle design. Thus, there typically is no capability to optimize strategies, taking account of variation in vehicle capabilities and limitations. A VOM learning capability was developed to optimize control inputs for the swing-to-pile task of a trenching operation. Different control strategies consisted of varied combinations of speed control, position control, and coast.

Abstract A number of semi-deterministic and stochastic formulations of multi-degree of freedom, frequency domain load models for heavy truck chassis are proposed and evaluated. The semi-deterministic models aim at reproducing the damage of a specific vehicle, while the stochastic ones aim to describe a collection of vehicle loads. The stochastic models are divided into two groups: Monte Carlo based and models based on single spectrum matrices. In both cases, the objective is to provide a load model that may be used to produce a design with a certain probability of survival. The goodness of the models is evaluated through a comparison of their damage outcomes with the corresponding damages of a set of time domain loads. This original time domain load set consists of chassis accelerations collected from seven physical trucks.

Abstract Electric heavy-duty tractor-trailers (EHDTT) offer an important option to reduce greenhouse gases (GHG) for the transportation sector. However, to increase the range of the EHDTT, this effort investigates critical vehicle design features that demonstrate a gain in overall freight efficiency of the vehicle. Specifically, factors affecting aerodynamics, rolling resistance, and gross vehicle weight are essential to arrive at practical input parameters for a comprehensive numerical model of the EHDTT, developed by the authors in a subsequent paper. For example, drag reduction devices like skirts, deturbulators, vortex generators, covers, and other commercially available apparatuses result in an aggregated coefficient of drag of 0.367. Furthermore, a mixed utilization of single-wide tires and dual tires allows for an optimized trade-off between low rolling resistance tires, traction, and durability.

Abstract Vehicle rolling resistance and weight are two of the factors that affect fuel economy. The vehicle tire rolling resistance has a more significant influence than aerodynamics drags on fuel economy at lower vehicle speeds, particularly true for medium- and heavy-duty trucks. Less vehicle weight reduces inertia loads, uphill grade resistance, and rolling resistance. The influence of weight on the fuel economy can be considerable particularly in light- to medium-duty truck classes because the weight makes up a larger portion of gross vehicle weight. This article presents an empirical investigation and a numerical analysis of the influences of rolling resistance and weight on the fuel economy of medium-duty trucks. The experimental tests include various tires and payloads applied on a total of 21vehicle configurations over three road profiles. These tests are used to assess the sensitivity of rolling resistance and weight to the vehicle fuel economy.

Abstract An accurate and rapid thermal model of an axle-brake system is crucial to the design process of reliable braking systems. Proper thermal management is necessary to avoid damaging effects, such as brake fade, thermal cracking, and lubricating oil degradation. In order to understand the thermal effects inside of a lubricated braking system, it is common to use Computational Fluid Dynamics (CFD) to calculate the heat generation and rejection. However, this is a difficult and time-consuming process, especially when trying to optimize a braking system. This article uses the results from several CFD runs to train a Stacked Ensemble Model (SEM), which allows the use of machine learning (ML) to predict the systems’ temperature based on several input design parameters. The robustness of the SEM was evaluated using uncertainty quantification.

Abstract This paper presents a combined aero-thermal computational fluid dynamic (CFD) evaluation of platooning medium duty commercial vehicles in two highway configurations. Thermal analysis comparison is made between an approach that includes vehicle drag reduction on engine heat rejection and one that does not by assuming a constant heat rejection based on open road conditions. The paper concludes that accounting for aerodynamic drag reduction on engine heat load provides a more real world evaluation than assuming a constant heat load based on open road conditions. A 3D CFD underhood thermal simulations are performed in two different vehicle platooning configurations; (i) single-lane and (ii) two-lane traffic conditions. The vehicle platooning consists of two identical vehicles, i.e. leading and trailing vehicle. In this work, heat exchangers are modeled by two different heat rejection rate models.

Abstract An analysis method for the stability of combined braking system of tractor-semitrailer based on phase-plane is investigated. Based on a 9 degree of freedom model, considering longitudinal load transfer, nonlinear model of tire and other factors, the braking stability of tractor-semitrailer is analyzed graphically on the phase plane. The stability of both tractor and semitrailer with different retarder gear is validated with the energy plane, β plane, yaw angle plane and hinged angle plane. The result indicates that in the long downhill with curve condition, both tractor and semitrailer show good stability when retarder is working at 1st and 2nd gear, and when it is at 3rd gear, the tractor is close to be unstable while semitrailer is unstable already. Besides, tractor and semitrailer both lose stability when retarder is working at the 4th gear.

Abstract This article focuses on the development of a two-way coupled methodology to predict gear temperature of oil jet lubricated transmissions using commercial software for computational fluid dynamics simulation. The proposed methodology applies an overset mesh technique to model the gear interlocking motion, multiphase of air-oil mixture, and heat transfer. Two gear pairs were used to develop and validate the methodology, an overdrive helical gear pair of a commercial vehicle transmission and a standard spur gear pair. Different oil jet lubrication methods were investigated using the proposed methodology, such as oil jet directed at the into-mesh position and at the out-of-mesh position. This investigation showed that out of mesh lubrication direction shows better cooling performance which is in well agreement with previous studies of literature.

Abstract The selective catalytic reduction (SCR) of nitrogen oxides seems to be the most promising technique to meet prospective emission regulations of diesel-driven commercial vehicles. In the case of developing cost-effective catalytic converters with comparably high activity, selectivity, and resistance against aging, ion-exchanged zeolites play a major role. This study presents, firstly, a brief literature review and subsequently a discussion of an extensive conversion analysis of exemplary Cu/ and Fe/zeolites, as well as a homogeneous admixture of both. The aging stages of SCR catalysts deserve particular attention in this study. In addition, the aging condition of the diesel oxidation catalyst (DOC) was analyzed, which influences the nitrogen dioxide (NO2) formation, because the NO2/nitrogen oxides (NOx) ratio upstream from the SCR converter could be identified as a key factor for low temperature NOx conversion.

Abstract Powertrain simulations and catalyst studies showed the efficiency credits and feasibility of onboard reforming as a way to recover waste heat from heavy duty vehicles (HDVs) fueled by natural gas (NG). Onboard reforming involves 1) injecting NG into the exhaust gas recycle (EGR) loop of the HDV, 2) reforming NG on a catalyst in the EGR loop to hydrogen and carbon monoxide, and 3) combusting the reformed fuel in the engine. The reformed fuel has increased heating value (4-10% higher LHV) and flame speed over NG, allowing stable flames in spark ignition (SI) engines at EGR levels up to 25-30%. A sulfur-tolerant reforming catalyst was shown to reform a significant amount of NG (15-30% conversion) using amounts of precious metal near the current practice for HDV emissions control (10 g rhodium). Engine simulations showed that the high EGR levels enabled by onboard reforming are used most effectively to control engine load instead of waste-gating or throttling.