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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 The vehicle attributes developed for emerging markets like India are unique because of different topographical conditions, diversity and culture within the different states. Major attributes in vehicle development process is development of safe and sustainable vehicle systems (steering, brakes etc.) for the driver. India is presently an emerging market for automotive sector. With booming economy, purchasing power of the consumer has gone up in the past few years. Most of young population of India have started buying the cars. At the same time, India’s road infrastructure, vehicle regulations have exalted over the years. The consumer cognizance towards the vehicles have started changing now. They want safer, robust system in their vehicles with new convenience features at affordable cost. In recent years, almost all OEM’s in India have migrated steering systems from HPAS to EPAS for payback on fuel economy and weight.

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 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 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 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 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 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.

Abstract The study of road loads on trucks plays a major role in assessing the effect of heavy-vehicle design on fuel conservation measures. Coastdown testing with full-scale vehicles in the field offers a good avenue to extract drag components, provided that random instrumentation faults and biased environmental conditions do not introduce errors into the results. However, full-scale coastdown testing is expensive, and environmental biases which are ever-present are difficult to control in the results reduction. Procedures introduced to overcome the shortcomings of full-scale field testing, such as wind tunnels and computational fluid dynamics (CFD), though very reliable, mainly focus on estimating the effects of aerodynamic drag forces to the neglect of other road loads which should be considered.

Abstract Commercial vehicles often incorporate self-steering axles to meet the axle load requirements while providing improved maneuverability, reduced off-tracking, and reduced tire and pavement wear. Market forces promote the design of more efficient self-steering axle products with reduced weight and more features. Manufacturers also work to differentiate their products through unique designs and new concepts. Traditional design methods for self-steering axles include empirical and trial-and-error methods to set the steering mechanism design parameters based on known design baselines and prior experience. For innovative new concepts that are too far from the traditional designs, it is desirable to have alternative ways for evaluating the expected performance. This article introduces a reduced-order model that allows the rapid analysis of the steering dynamic behavior of self-steering axles.

Abstract Truck crashes on Wyoming mountain passes due to brake heating has been a long-standing issue due to the steep downgrades that characterize some routes in the state. The grade severity rating system (GSRS) developed by the Federal Highway Administration (FHWA) to recommend maximum safe speeds has been identified as a viable countermeasure to reducing the incidence of downgrade truck crashes. However, several decades have passed since the GSRS was developed. In the decades since its development, truck features have undergone radical changes in terms of design. The streamlined design of tractors and trailers, use of drag reduction devices, changes in engine features, and adoption of radial tires have led to a reduction in the non-brake forces that retard motion. Truck brakes have also changed along with retarder characteristics. This has meant that maximum safe speeds recommended by the GSRS have been conservative.

Abstract In this article, an adaptive state estimation algorithm for precise air-fuel ratio (AFR) control is presented. AFR control is a critical part of internal combustion engine (ICE) control, and tight AFR control delivers lower engine emissions, better engine fuel economy, and better engine transient performance. The proposed control algorithm significantly improves transient AFR control to eliminate and reduce the amplitude of the lean and rich spikes during transients. The new algorithm is first demonstrated in simulation (using Matlab/SimulinkTM and GT-PowerTM) and then verified on a test engine. The engine tests are conducted using the European Transient Cycle (ETC) with HoribaTM double-ended dynamometer. The developed algorithm utilizes a nonlinear physics-based engine model in the observer and advanced control principles with modifications to solve real industrial control issues.

Abstract Brake systems are one of the essential components of vehicles ensuring the safety of roads and passengers as well as accident prevention. Faulty brake systems, however, can cause inevitable accidents. Fatality analysis reporting system of NHTSA (National Highway Transport Safety Association) has reported that heavy and light trucks, which are obliged to be equipped with dual-circuit air brake system, were, respectively, involved in 8.8% and 38.0% of fatal crashes in the United States, during 2017. Number of heavy vehicle accidents due to complete failure of brake system is far less than accidents due to deficiencies such as worn out brake linings, out-of-adjustment push rod strokes, and leak in the circuits. Severe leakages due to ruptured air hoses or punctured reservoir are highly unlikely to be replenished by compressor and would be distinguished through pressure indicator.

Abstract Diesel trucks play a crucial role in transportation activity and a major contributor to fuel consumption and air pollution. To improve the energy efficiency of diesel trucks, we develop a truck eco-approach and departure (EAD) system based on Signal Phase and Timing (SPaT) message from signal controllers and road grade information along the path. The proposed model consists of two levels—the lower level for powertrain-based fuel consumption estimation and the upper level for optimal trajectory planning. The powertrain model is designed for a diesel engine with a six-gear transmission and well calibrated using on-board Electronic Control Unit (ECU) data. The trajectory planning model is formulated as a shortest path problem with the combination of time, distance, and speed as the state on each node and fuel consumption rate as the cost on state transition.