Research on automatic emergency braking (AEB) control algorithms for heavy vehicles is relatively limited. Compared with passenger cars, heavy vehicle AEB algorithms must accommodate both unloaded and fully loaded conditions, with the latter posing higher demands. This study compares two distinct AEB control strategies: the time-to-collision (TTC) algorithm and the professional driver fitted (PDF) algorithm. Using simulation analyses under three regulatory-recommended scenarios—stationary lead vehicle, slow-moving lead vehicle, and decelerating lead vehicle—the results indicate that the PDF-based control system better adapts to both unloaded and fully loaded conditions. It demonstrates significant improvements in braking performance and robustness compared to the TTC-based system. For an unloaded vehicle equipped with the PDF–AEB control system (5500 kg), the final gap to the lead vehicle is the longest (11.5 m) under the scenario of a stationary lead vehicle with an initial ego vehicle speed of 80 km/h and the shortest (3.1 m) under the scenario of a lead vehicle with an initial speed of 50 km/h braking at 0.4 g. For a fully loaded vehicle (12,500 kg), the corresponding final gaps to the lead vehicle are 11.2 m and 2.5 m, respectively.
As tractor-trailers are essential to global logistics, their roll stability during emergency maneuvers is a critical safety concern. This paper presents a novel delay-compensated active roll control strategy for tractor-trailers using a two-dimensional piston pump electro-hydrostatic actuator (EHA). Unlike existing advanced strategies that assume ideal actuator behavior, this approach specifically targets the inherent response delay in high-tonnage applications. A detailed EHA model, including pump flow characteristics and hydraulic mechanics, was developed and validated through step response experiments. A seven-degree-of-freedom vehicle dynamics model and a model predictive controller were also constructed to compute the required anti-roll moment under emergency driving conditions. In order to address the EHA actuator’s response delay, a delay feedforward controller (DFC) was designed, integrating acceleration feedforward, feedback regulation, and delay disturbance estimation. TruckSim–Simulink co-simulations under double lane-change (DLC) maneuvers at 40 km/h, 60 km/h, and 80 km/h show that DFC improves displacement tracking and reduces peak trailer roll angle by up to 15% compared to a velocity-feedforward proportional-integral-derivative (VFPID) controller. It also enhances control efficiency, as evidenced by lower average motor speeds and pressure response of EHA. The system demonstrates high power-to-weight ratio and efficient tracking capabilities under dynamic conditions. Although active control provides limited benefit at low speeds, the proposed strategy effectively improves roll stability and driving safety under dynamic conditions.
Agricultural vehicles operating in rough environments experience increased fatigue damage accumulation, which may decrease machine safety and reliability. Autonomous agricultural machines offer an opportunity to incorporate fatigue damage considerations into path planning. This work investigates whether machine learning can predict fatigue damage to a tractor chassis using light detection and ranging (LiDAR)-based terrain features, vehicle speed, and rotational vehicle state data (e.g., triaxial angle, angular velocity, and angular acceleration). Fatigue damage was estimated using the Rupp filter and the Durability Transfer Concept. Following poor predictive performance of the machine learning models, an exploratory analysis of damage histograms, dominant frequency, and acceleration magnitude was performed. Results indicated that most estimated fatigue damage occurred in the 0–2 Hz band, which coincides with the frequency range of terrain-induced acceleration. On-road driving led to the greatest fatigue damage, potentially due to the harder driving surface and increased vehicle speed. Differences between root mean square (RMS) acceleration magnitude and fatigue damage indicate that isolated high-magnitude events may have contributed to increased estimated fatigue damage. Several suggestions for future development were identified. Identification of the endurance limit of the tractor chassis will permit the removal of nondamaging events, improving label accuracy. Furthermore, the presence of a front-loader implement may have impacted chassis acceleration. Thus, a comprehensive dataset with multiple implement configurations is needed to determine the influence of implement configuration on dynamics and resultant damage.
A novel looped-freezing mean approach based on Detached Eddy Simulation (DES) approach is developed in context of assessing underhood cooling performance in heavy-duty vehicles. The method involves computing a temporally averaged flow field from DES simulations, which is then frozen and used by the energy solver to predict temperature distributions. This process is iteratively repeated until a statistically steady-state temperature field is achieved. It is demonstrated that traditional DES approach demonstrates superior accuracy in capturing forced convection heat transfer compared to the Reynolds-Averaged Navier–Stokes (RANS) method. The validation against experimental data for flow over a heated sphere at a Reynolds number of 105 shows that DES yields Nusselt numbers with better correlation than RANS. However, it is observed that DES approach captures unsteady flow features that introduce temporal fluctuations in heat transfer. In the context of underhood cooling evaluations where properties of the fluid are strong functions of temperature and coupled with iterative processes such as dual-stream heat-exchanger modeling, these instabilities can frequently lead to numerical divergence of the simulation. The novel looped-freezing mean DES method is then applied to a reduced underhood model, including the heat exchanger and fan assembly, bounded by walls representing adjacent vehicle components. The study show that the novel looped-freezing mean DES approach provides stable and converged thermal predictions for the reduced underhood model. This approach is particularly beneficial for simulations involving highly transient flow fields coupled with thermal phenomena, enabling accurate and reportable temperature evaluations in critical regions.
Decarbonization efforts achieved through electrification in nonroad mobile machinery can realize a reduction in fuel consumption of more than 20%, thanks to concepts familiar to light-duty passenger vehicles. This case study compares the results of a hybrid-electric material handler to its conventional counterpart, utilizing machine-specific drive cycles presented in part one of this paper series. The hybrid prototype features an extended-range electric vehicle (EREV) powertrain that demonstrated substantial energy efficiency improvements. Specifically, there was a reduction in equivalent fuel consumption of 75% when operating in electric-only mode, and 33% when maintaining the battery by charging with an on-board generator. Together, the efficiency improvements can be extrapolated over a low-intensity, 8-h shift characterized by significant idle time and highly dynamic engine load for a 47% reduction in net energy consumption. Key technologies that led to this improvement included engine downsizing and decoupling, regenerative braking, and an electrohydraulic pump unit with advanced controls. This study explains details of the powertrain architecture and subsystems that were implemented on a demonstration vehicle, control strategies used to meet project goals, and an analysis of energy consumption from testing on a closed course. Also included in this study is a discourse on comparison metrics that can be used for quantifying the energy consumption differences between hybrid-electric and conventional diesel powertrains in nonroad mobile machinery.
Knowing a detailed operating cycle is critical for developing and testing equipment. Operating cycles can be separated by two clear distinctions: (1) regulatory or non-regulatory and (2) application at the engine-only or full machine level. The Environmental Protection Agency’s (EPA) Nonroad Transient Cycle (NRTC) may be a good representation of engine use in many types of equipment, but there is a gap in standardized and validated drive cycles specifically for nonroad material handlers. Lacking a standardized drive cycle makes it difficult to accurately benchmark machine performance and validate new powertrain technologies. The objective of this investigation is to illustrate the development of a custom drive cycle augmented with real-world customer use data that serves multiple purposes: (1) understand the range of operation and utilization that formulated inputs for electrified architecture analysis and (2) develop a repetitive and consistent maneuver to establish baseline energy consumption enabling equivalent comparison to future electrified prototype builds. This article presents a solution specifically for a 23-ton nonroad material handler in which material handling, machine transport, and extended idle were homologated to form representative short cycles defined by machine velocity and hydraulic cylinder position. The most intensive material handling short cycles had a load factor of 40% and an average fuel rate of 16 L/h. Combined with a visual aid, the short cycles exhibited low variability, having less than 5% root mean square (RMS) error in lift and reach position with respect to the average. The machine’s performance on these short cycles at the Advanced Power Systems Research Center (APSRC) was compared to results from two real-world customer locations operating the instrumented test machine in a cyclical manner, and for similar ground conditions were found to be comparable in fuel consumption.
In order to improve the comfort performance in commercial vehicles, this study proposes a hierarchical control strategy that integrates the evaluation and migration of control algorithms. First, a quarter-vehicle model with four-degree-of-freedom (4-DOF) is constructed, incorporating the dynamics of the wheel, frame, driver’s cab, and seat. The key modal characteristics of the model are then verified through amplitude–frequency analysis, confirming their consistency with the typical vibration patterns observed in actual commercial vehicles, which provides the foundation for subsequent control strategy evaluation and migration. Then, based on a standard two-degree-of-freedom (2-DOF) suspension model, a weighted comprehensive evaluation function is developed to account for comfort, structural safety, handling stability, and both time- and frequency-domain performance indicators. Using this evaluation function, various control algorithms—including Skyhook control (SH), acceleration-based damping control (ADD), and proportional–integral–derivative control (PID)—are systematically assessed. The control algorithm is migrated to the 4-DOF model to carry out the hierarchical collaborative control. The results show that this method can effectively inhibit vibration transmission to enhance ride comfort and improve structural safety at the same time, while maintaining an acceptable level of handling performance. The transferability and applicability of the hierarchical control method are validated for the considered vertical dynamics scenarios. This article provides a new theoretical method and technical pathway for the comfort-oriented performance optimization of commercial vehicles.
To address the rollover risk of six-axle semi-trailers due to their large mass, high center of gravity, and multi-axle articulation, a lateral force balance anti-rollover strategy based on the Ackermann steering principle is proposed. By establishing the wheel angle constraint equations for the full-wheel steering system of the six-axle semi-trailer, a rigid-body dynamic model considering the articulation characteristics is developed. The key control and observation parameters are included in the wheel angles, center of gravity lateral offset, yaw angular velocity, sideslip angle, and lateral load transfer rate. An SMC-PID joint controller is designed, in which the third axle steering angle of the tractor is optimized by the SMC controller, and the trailer’s three-axle steering angle tracking control is achieved by the PID controller. The nonlinear accumulation of centrifugal force and dynamic load transfer under high-speed emergency lane change conditions is suppressed by a hierarchical control mechanism. The joint simulation results from TruckSim and Simulink indicate that, under the double lane change scenario with 88 km/h, the lateral force balance strategy reduces the rollover angles of the tractor and trailer by 85.5% and 86.9%, respectively, and the center of gravity lateral offset is improved by 77.5% and 92.3%; under the double lane change scenario with 80 km/h, compared with the active steering strategy of the trailer, the lateral load transfer rate fluctuation is reduced to the percentile level, and the rollover angles decrease by 62.9% and 65.3%.
In class 8 semi-trucks, the hydraulic steering gear and torque overlay system are critical components affecting the steering feel design and vehicle control. Transitioning from traditional hydraulic gears to hydraulic gears with torque overlay steering (TOS) systems for increased enhancement of driver comfort is beneficial but has also resulted in drawbacks for on-center steer feel, especially at high vehicle speeds (60+ km/h). This article evaluates the impact of three design mechanisms within hydraulic steering gears of a TOS system that have shown improvement in on-center performance for traditional hydraulic gears. The study compares a standard assembly of TOS, i.e., baseline, and a design-optimized ideal prototype, to evaluate the effectiveness of the three design mechanisms: valve curve performance, on-center friction, and torsion bar stiffness. The two samples underwent high-speed vehicle testing to gather driver feedback and assess potential enhancements to the on-center steering feel. The final design changes on the ideal prototype were based on the best valve curve and on-center friction, as limitations in the torsion bar modification process precluded its use in the vehicle. The vehicle qualification team found insufficient evidence linking these design features to improved overall steering performance. Further research will be conducted to analyze the impact of torsion bar change as well as software controller performance within the TOS as a follow-up study.
This study presents a structured approach to the aerodynamic evaluation of commercial heavy-duty vehicles by categorizing the underlying flow physics into three primary phenomena: pressure-induced separation, geometry-induced separation, and flow diffusion. Furthermore, the study gives insights into the benefits of Detached Eddy Simulations (DES) over traditional Reynolds-Averaged Navier–Stokes (RANS) approaches by analyzing the flow behavior in cases that correspond to these phenomena. Fundamental insights on pressure and geometry-induced separation were developed through simulations of flow over a sphere and a rectangular cylinder at a Reynolds number of 2.8 × 106. Additionally, flow diffusion was investigated using a coaxial jet interacting with surrounding fluid at a Reynolds number of 2.1 × 104. These cases were analyzed using three turbulence modeling techniques: k-ε, k-ω SST, and DES. To demonstrate the practical relevance of these phenomena, a comprehensive aerodynamic performance study was conducted on a commercial heavy-duty truck. This final analysis integrates all three flow behaviors, showcasing their combined impact on vehicle aerodynamics. The study emphasizes the effectiveness of the DES approach in capturing complex flow structures with enhanced accuracy. Furthermore, this study provides meshing guidelines for near-wall and wake dominant regions, to be implemented in DES-based simulations. The findings aim to support future research by offering a robust framework for applying advanced turbulence models in real-world aerodynamic evaluations.
This study investigates noise, vibration, and harshness (NVH) characteristics of hydraulic steering systems in medium- and heavy-duty commercial vehicles due to hydraulic system design. Utilizing on-vehicle and lab environment testing, primarily a pressure sweep test and speed sweep test, to identify sources of NVH. Testing demonstrated a significant impact to perceptible noise and vibration through changes to system and component design. NVH mitigation is accomplished by reducing pressure pulsations, cavitation, and turbulence within the fluid by changing hydraulic plumbing diameter. Reduction in sound pressure level (SPL) averaged 30% with peak reduction of 75%. While optimizing hose diameter is an effective method for controlling NVH in commercial vehicle hydraulic steering systems, additional studies should be conducted in optimizing plumbing materials and routing.
The vibrating half-car model is used to represent the dynamic behavior of a truck’s dependent suspension system, capturing four degrees of freedom. This research investigates time and frequency responses of vibration behavior of half-car model with possible tire–road separation. This investigation is significant because all previously reported analyses based on the tire-road attachment were incorrect, particularly regarding the tire-road separation phenomenon. The differential equations are extended to enhance the accuracy of the model, incorporating tire–road separation conditions for both wheels. A numerical approach is applied to simulate the vertical and roll dynamics of the system under the separation assumption. The simulation results are validated through experiments conducted using ADAMS View software. Integrating the tire–road separation into the model results in dynamic responses that closely reflect real-world behavior. These findings provide valuable guidance for designing more effective suspension systems and for developing control strategies aimed at reducing rollover risk and enhancing lateral stability.
This research primarily addresses the issue of resistance model setting for chassis dynamometers or EIL (engine-hardware-in-the-loop) systems under various loads. Based on the data available from the heavy-duty commercial vehicle coast-down test reports, this article proposes three methods for estimating coasting resistance. For heavy-duty commercial vehicles that have not undergone the coast-down test, this article proposes the GA-GRNN (AC) model to predict coasting resistance. Compared to the GA-BPNN model proposed by previous studies, the new model, which achieves 93% prediction accuracy, demonstrates higher estimation accuracy. For heavy-duty commercial vehicles that have undergone the coast-down test, the coasting equal power method proposed in this article can estimate the coasting resistance under various loads. The accuracy and stability of the new method are verified by several coast-down tests. Compared to the existing method proposed by existing scholars, the new method has a higher estimation accuracy, thus compensating for the limitations of the coast-down test in measuring the coasting resistance. When neural network is combined with the coasting equal power method, they not only overcome the limitations of neural network predictions for coasting resistance but also compensate for the limitations of the coasting equal power method in estimating coasting resistance. Ultimately, the methods proposed in this article provide a feasible solution for setting resistance models of chassis dynamometers or EIL systems under various loads, without relying on coast-down tests.
Power steering pumps are the heart of any hydraulic power steering system. They provide the heavy lifting power required in the form of high-pressure fluid flow that is utilized in powered steering gears or steering racks to assist drivers in vehicle maneuvers, specifically in low-speed situations. Failure of the power steering pump will inevitably increase work needed from the driver to steer a vehicle and decrease the driver comfort at the same time. This article covers investigations into a customer return issue, affecting more than 20% of pumps, for one particular failure mode, pump input shaft seal leakage, and how the failure is not caused by failure at the input shaft nor by failure of the input shaft seal. It was found that internal damage to the pump rotating assembly allows high-pressure oil to overcome the input shaft seal sealing effect. The cause of the failure was determined to be rooted in the manufacturing process, which was re-ordered to reduce the failure rate to an acceptable value (<1%).
In this article, the hybrid drive is discussed of the combination of conventional tractors with electrified trailers, usually referred to as E-trailer. We demonstrate that this approach offers the possibility of achieving fuel savings exceeding 20%. For regional trips, about half of this reduction is achieved without offline charging, i.e., without applying electric energy from the E-trailer battery. For motorway dominant trips, more use is required of the battery energy. A new control strategy is proposed, validated through simulations, in which only three control parameters are required, which can be tuned effectively to achieve maximum fuel reduction under certain trip and loading conditions. This control strategy adjusts the E-trailer torque request, based on the requested power for the tractor diesel engine, being estimated through a smart kingpin sensor. It ensures that the E-trailer supports the tractor propulsion when significant power is required, and recovers energy when the demand for power is low. The control parameters consist of the maximum torque request for the E-trailer during support, the maximum negative torque request during regeneration, and the transition power between regeneration and support. Semitrailers are generally not linked to a specific tractor. The control strategy is unique in that it does not need access to the tractor data network, thus achieving optimum interchangeability. The sensitivity with respect to driving resistance parameters appears to be low and may be counteracted by tuning the control parameters. More care is needed for the assessment of the trailer mass and trailer center of gravity. Finally, the total fuel reduction is discussed in comparison to the charging costs for the E-trailer battery (cost–benefit analysis), for realistic cost levels for fuel and kWh.
Rollover protective structures (ROPS) that absorb energy during vehicle rollovers play a crucial role in providing integrated passive safety for operators restrained by seat belts. These protective structures, integrated into the vehicle frame, are designed to absorb high-impact energy and deform in a controlled manner without intruding into the occupant’s safe zone. This research focuses on the detailed analytical design procedure and performance evaluation criteria of the two-post open ROPS used on motor graders against lateral loads. An experimental test on a standard tubular square hollow section (SHS) column subjected to lateral load has demonstrated a significant correlation between the post-yield behavior of plastic hinge development and energy absorption, compared with results from various formulations adopted in finite element analysis (FEA). To reduce design iteration time and the cost of physical destructive testing, the complete equipment experimental setup is virtually simulated, building upon a thorough understanding of plastic hinge formation on columns under large deflections. This simulation provides comprehensive insights into the structural elasto-plastic response and employs the nonlinear implicit and explicit schemes of FEA to accurately predict energy absorption and force vs deflection behavior. The study follows the guidance outlined in ISO 3471: 2008 standard specifications, validating key structural performance parameters through virtual CAE simulation to ensure alignment with the standard’s force and energy requirements. The research emphasizes the control of merging empirical and analytical methods with advanced CAE tools, allowing engineers to design and evaluate ROPS with superior energy absorption and minimal deflection. By adopting this holistic approach, designers can significantly enhance ROPS structural integrity, ensuring improved safety and protection for operators in the demanding conditions of off-highway vehicles.
This article aims to analyze and evaluate the roll safety thresholds (RSTs) and roll safety zones of tractor semi-trailer vehicles during turning maneuvers, using the roll safety factor (RSF) and yaw rate of the vehicle bodies. To achieve this, a full dynamics model is established using the multibody system method. This model is then used to survey and evaluate the vehicle's motion state, using ramp steer maneuver (RSM) steering rules. In each survey case, the maximum values of RSF and yaw rate of vehicle bodies are synthesized in 3D data, with an initial velocity range of 40 km/h to 80 km/h and a magnitude of steering wheel angle range of 12.5 degrees to 300 degrees. These 3D data are used to determine the proposed values of RSF, which can be used as examples to set the threshold values of the yaw rate of vehicle bodies and roll safety zones. At a velocity of 60 km/h, the dynamic rollover threshold for proposed roll safety factor (RSFprop) is equal to 1, with corresponding values of 15.718 degrees/s and 14.962 degrees/s. Similarly, the warning threshold for RSFprop is equal to 0.6, with values of 9.514 degrees/s and 9.404 degrees/s, and for RSFprop equal to 0.7, the values are 10.705 degrees/s and 10.625 degrees/s. The control threshold for a vehicle velocity of 60 km/h and RSFprop equal to 0.9 is calculated as 13.588 degrees/s and 13.339 degrees/s. These results can be used as a basis for developing early warning and control systems for various vehicle operating modes.
Analyzing and accurately estimating the energy consumption of battery electric buses (BEBs) is essential as it directly impacts battery aging. As fleet electrification of transit agencies (TAs) is on the rise, they must take into account battery aging, since the battery accounts for nearly a quarter of the total bus cost. Understanding the strain placed on batteries during day-to-day operations will allow TAs to implement best-use practices, continue successful fleet electrification, and prolong battery life. The main objective of this research is to estimate and analyze the energy consumption of BEBs based on ambient conditions, geographical location, and driver behavior. This article presents a model for estimating the battery energy consumption of BEBs, which is validated using the data on federal transit bus performance tests performed by Penn State University and experimental aggregated trip data provided by the Central Ohio Transit Authority (COTA). The developed simulator aims to realistically estimate the actual BEB energy consumption, including factors that are difficult to account for, such as the weather conditions, driver behavior, and uncertain passenger load along a route. The results of the model are compared to results from Penn State University, COTA aggregated trip data, and other methodologies for energy consumption estimation. Finally, the impact of seasonal weather variations and driver aggressiveness on the energy consumption is assessed through simulation analyses.
