Browse Topic: Trucks

Items (5,932)
This work presents a computationally inexpensive but effective method for an initial assessment of component sizing and power-split for fuel cell hybrid electric heavy-duty trucks. As a first step, the proposed method employs a prototypical longitudinal vehicle model to generate power demand at every instant of a representative drive cycle. Subsequently, six fuel cell and battery sizing combinations, each providing a peak continuous system power of 400 kW, are identified based on drive cycle power demands, commercially available fuel cell sizes, and Department of Energy (DOE) sizing targets. Ultimately, for each sizing combination, a proportional-integral (PI) controller with anti-windup is implemented to split power between the fuel cell and battery. In this study, the controller is tuned to reduce hydrogen consumption while meeting the instantaneous power demand and maintaining the battery state-of-charge (SOC) between 0.3 and 0.7. The results indicate that increasing the fuel cell
Mandviwala, AliYesilyurt, SerhatStefanopoulou, Anna
In addition to electric vehicles (EVs), hydrogen fuel cell systems are gaining attention as energy-efficient propulsion options. However, designing fuel cell vehicles presents unique challenges, particularly in terms of storage systems for heavy hydrogen tanks. These challenges impact factors such as NVH (noise, vibration, and harshness) and safety performance. This study presents a topology optimization study for Hydrogen Energy Storage System (HESS) tank structure in Class 5 trucks, with a focus on enhancing the modal frequencies. The study considers a specific truck configuration with a HESS structure located behind the crew cab, consisting of two horizontally stacked hydrogen tanks and two tanks attached on both sides of the frame. The optimization process aimed to meet the modal targets of this hydrogen tank structure in the fore-aft (X) and lateral (Y) directions, while considering other load cases such as a simplified representation of GST (global static torsion), simplified
Yoo, Dong YeonChavare, SudeepViswanathan, SankarMouyianis, Adam
As a distributed wire control brake system, the electro-mechanical brake (EMB) may face challenges due to the need to integrate the actuator in the limited space beside the wheel. During extended downhill braking, especially on wet roads with reduced adhesion, the EMB must operate at high intensity. The significant heat generated by friction can lead to thermal deformation of components, such as the lead screw, compromising braking stability. This paper focuses on pure electric light trucks and proposes a tandem composite braking method. This approach uses an eddy current retarder (ECR) or motor to provide basic braking torque, while the EMB supplies the dynamic portion of the braking torque, thereby alleviating the braking pressure on the EMB. First, a driver model, tire model, motor model, and braking models are developed based on the vehicle's longitudinal dynamics. In addition, the impact of various factors, such as rainfall intensity, road slope, ramp length and vehicle speed, on
Liu, WangZhang, YuXiao, HongbiaoShen, Leiming
Both automotive aftermarket vehicle modifications and Advanced Driver Assistance Systems (ADAS) are growing. However, there is very little information available in the public domain about the effect of aftermarket modifications on ADAS functionality. To address this deficiency, a research study was previously performed in which a 2022 Chevrolet Silverado 1500 light truck was tested in four different hardware configurations. These included stock as well as three typical aftermarket configurations comprised of increased tire diameters, a suspension level kit, and two different suspension lift kits. Physical tests were carried out to investigate ADAS performance of lane keeping, crash imminent braking, traffic jam assist, blind spot detection, and rear cross traffic alert systems. The results of the Silverado study showed that the ADAS functionality of that vehicle was not significantly altered by aftermarket modifications. To determine if the results of the Silverado study were
Bastiaan, JenniferMuller, MikeMorales, Luis
Headlight glare remains a persistent problem to the U.S. driving public. Over the past 30 years, vehicle forward lighting and signaling systems have evolved dramatically in terms of styling and lighting technologies used. Importantly, vehicles driven in the U.S. have increased in size during this time as the proportion of pickup trucks and sport-utility vehicles (SUVs) has increased relative to passenger sedans and other lower-height vehicles. Accordingly, estimates of typical driver eye height and the height of lighting and signaling equipment on vehicles from one or two decades ago are unlikely to represent the characteristics of current vehicles in the U.S. automotive market. In the present study we surveyed the most popular vehicles sold in the U.S. and carried out evaluations of the heights of lighting and signaling systems, as well as typical driver eye heights based on male and female drivers. These data may be of use to those interested in understanding how exposure to vehicle
Bullough, John D.
Reducing aerodynamic drag through Vehicle-Following is one of the energy reduction methods for connected and automated vehicles with advanced perception systems. This paper presents the results of an investigation aimed at assessing energy reduction in light-duty vehicles through on-road tests of reducing the aerodynamic drag by Vehicle-Following. This study provides insights into the effects of lateral positioning in addition to intervehicle distance and vehicle speed, and the profile of the lead vehicle. A series of tests were conducted to analyze the impact of these factors, conducted under realistic driving conditions. The research encompasses various light-duty vehicle models and configurations, with advanced instrumentation and data collection techniques employed to quantify energy-saving potential. The study featured two sets of L4 capable light duty vehicles, including the Stellantis Pacifica PHEV minivan and Stellantis RAM Truck, examined in various lead and following vehicle
Poovalappil, AmanRobare, AndrewSchexnaydre, LoganSanthosh, PruthwirajBahramgiri, MojtabaBos, Jeremy P.Chen, BoNaber, JeffreyRobinette, Darrell
With the increasing prevalence of electric vehicles (EVs), decreasing vehicle drag is of upmost importance, as range is a primary consideration for customers and has a direct bearing on the cost of the vehicle. While the relationship between drag and range is well understood, there exists a discrepancy between the label range and the real-world range experienced by customers. One of the factors influencing the difference is the ambient wind condition that modifies the resultant air speed and yaw angle, which is typically minimized during SAE coast-down testing. The following study implements a singular wind-averaged drag (WAD) coefficient which is derived from a 3-point yaw curve to show the impact of yaw as compared to the zero-yaw condition. This leads to an interesting dilemma for the vehicle aerodynamicist: whether to optimize the vehicle's exterior shape for low wind (zero yaw) conditions or for real-world conditions where the ambient wind generally produces a few degrees of yaw
Kaminski, MeghanD'Hooge, AndrewBorton, Zackery
This study evaluates the performance of alternative powertrains for Class 8 heavy-duty trucks under various real-world driving conditions, cargo loads, and operating ranges. Energy consumption, greenhouse gas emissions, and the Levelized Cost of Driving (LCOD) were assessed for different powertrain technologies in 2024, 2035, and 2050, considering anticipated technological advancements. The analysis employed simulation models that accurately reflect vehicle dynamics, powertrain components, and energy storage systems, leveraging real-world driving data. An integrated simulation workflow was implemented using Argonne National Laboratory's POLARIS, SVTrip, Autonomie, and TechScape software. Additionally, a sensitivity analysis was performed to assess how fluctuations in energy and fuel costs impact the cost-effectiveness of various powertrain options. By 2035, battery electric trucks (BEVs) demonstrate strong cost competitiveness in the 0-250 mile and 250-500 mile ranges, especially when
Mansour, CharbelBou Gebrael, JulienKancharla, AmarendraFreyermuth, VincentIslam, Ehsan SabriVijayagopal, RamSahin, OlcayZuniga, NataliaNieto Prada, DanielaAlhajjar, MichelRousseau, AymericBorhan, HoseinaliEl Ganaoui-Mourlan, Ouafae
A heavy-duty commercial electric truck is equipped with dual axles, with the middle axle driven by an electric motor and a three-speed transmission and the rear axle driven by an electric motor and a two-speed transmission. To consider the dynamic and economy performance of the whole vehicle, as well as the gear distribution characteristics in the vehicle operation, a comprehensive shifting schedule based on the cross-particle swarm algorithm is proposed. By establishing the longitudinal dynamics model of the truck, the optimal power shift schedule and the optimal economics shift schedule of each of the two transmissions are studied. Under the standard test conditions, an optimal gear control strategy based on the dynamic programming algorithm considering the shift interval is proposed, and the shift schedule for the standard conditions is derived through the hierarchical clustering method. Furthermore, with 0-100 km/h acceleration capability and specific energy consumption as the
Guo, JunZhang, YunqingWu, Jinglai
This study presents a detailed techno-economic assessment of battery-electric trucks, incorporating battery aging effects within a total cost of ownership (TCO) model. With increasingly stringent emissions regulations, battery-electric trucks are becoming a viable solution in Europe. However, due to uncertainty regarding their long-term cost-effectiveness and fleet operators’ profit-oriented priorities, there is an urgent need for accurate TCO assessment. Existing studies often overlook or oversimplify the impact of battery aging on overall costs. This work addresses this gap by introducing battery aging-related costs through an empirical battery degradation model, evaluated over the vehicle’s lifetime. Key aging costs include a refined estimation of battery residual value, influenced by degradation and remaining battery life, and potential battery replacement expenses. A case study on a VECTO group 9 truck used for regional delivery missions examines different payloads and battery
Costantino, TrentalessandroAcquarone, MatteoMiretti, FedericoSpessa, Ezio
This study evaluates the impacts of the gasoline compression ignition (GCI) engine on heavy duty long-haul trucks in both the Chinese and US markets. The study examines various aspects such as vehicle performance requirements, fuel consumption, emissions, and ownerships costs, and how they influence the implementation and impact of new technologies in these markets. By considering a wide variety of drive cycles, including standard regulatory cycles and real-world cycles, the study aims to identify the impact of varying degrees of powertrain electrification using diesel and GCI engines on fuel consumption and emissions. Additionally, this paper explores the viability of powertrain electrification in long-haul trucks by analyzing factors such as levelized cost of driving (LCOD), manufacturing costs, and energy costs. These considerations play a crucial role in determining the economic feasibility and attractiveness of electrification technologies in various driving scenarios and market
Nieto Prada, DanielaVijayagopal, RamYan, ZimingSari, RafaelHe, Xin
Diverse solutions will likely be needed to decarbonize the commercial truck sector in the United States. Battery-powered vehicles play a predominant role but in some cases, fuel cell trucks are more advantageous for the consumer. This study examines several medium- and heavy-duty applications designed for different driving range requirements to identify the design space where battery and fuel cell trucks are attractive. Also considered are the impacts of purchase price, fuel cost, and vehicle usage. We examine the top 10 truck classes as well as bus applications based on vehicle population, fuel usage, and driving distances. We assume a 2030 scenario where both batteries and FC systems become less costly and more efficient, as targeted by the U.S. Department of Energy. Even for smaller-class vehicles, where battery electric vehicles are expected to be the most economical among clean vehicle solutions, the results are not straightforward. Based on vehicle design, usage, and external
Vijayagopal, RamBirky, Alicia
Tractor-semitrailers play an important role in the transportation industry. However, global warming and the rapid advancement of energy technologies have driven the transformation of high-emission vehicles, such as tractor-semitrailers, to be powered by new energy sources in order to achieve goals related to energy conservation, emission reduction, and cost savings. By using the motor as the primary driving force, the energy recovered during braking or coasting can be converted into electricity and stored in the battery for later use. While much research has been conducted on braking control and energy recovery for passenger cars, there is limited research on tractor-semitrailers. Additionally, the jackknife is a critical factor to consider under high-speed conditions. To investigate the braking energy recovery of electric tractor-semitrailers, tire and motor models were developed based on the turning and braking conditions of such vehicles. Taking into account the load transfer effect
Chen, RunpingDuan, Yupeng
Electric trucks, due to their weight and payload, need a different layout than passenger electric vehicles (EVs). They require multiple motors or multi-speed transmissions, unlike passenger EVs that often use one motor or a single-speed transmission. This involves determining motor size, number of motors, gears, and gear ratios, complicated by the powertrain system’s nonlinearity. The paper proposes using a stochastic active learning approach (Bayesian optimization) to configure the motors and transmissions for optimal efficiency and performance. Backwards simulation is applied to determine the energy consumption and performance of the vehicle for a rapid simulation of different powertrain configurations. Bayesian optimization, was used to select the electric drive unit (EDU) design candidates for two driving scenarios, combined with a local optimization (dynamic programming) for torque split. By optimizing the electric motor and transmission gears, it is possible to reduce energy
Chen, BichengWellmann, ChristophXia, FeihongSavelsberg, ReneAndert, JakobPischinger, Stefan
The depletion of fossil fuels and the emergence of global warming propel public sectors to explore alternative energy such as renewable electricity and hydrogen to reduce greenhouse gas (GHG) emissions. Numerous studies have demonstrated substantial environmental benefits of electric light-duty vehicles. However, research focusing on heavy-duty vehicles is still relatively scarce, and the transition to zero emissions heavy-duty trucks is facing enormous technical and economic challenges. This work investigated GHG emissions during the manufacturing and assembly phase of heavy-duty vehicles (HDVs), including battery electric trucks (BETs) and gaseous hydrogen fuel cell electric trucks (FCETs) using SimaPro software package with wildly accepted Ecoinvent database based on UK grid mix scenarios. A comparative analysis of greenhouse gas (GHG) emissions during the production phase of 700 bar- and 350 bar-H2 FCETs and their battery electric counterparts (eqBETs) was conducted under two UK
Zhao, JianboLi, HuBabaie, MeisamLi, Kang
Marine ports are an important source of emissions in many urban areas, and many ports are implementing plans to reduce emissions and greenhouse gases using zero-emission cargo handling equipment. This paper evaluates the performance and activity profiles for various zero-emission (ZE) cargo transport equipment being demonstrated at different ports in California. This included 23 battery-electric (BE) 8,000 lb. (8K) and 36,000 lb. (36K) forklifts, a BE railcar mover, and an electrified rubber-tired gantry crane (eRTG). The study focused on evaluating the performance of the ZE equipment in terms of activity patterns and the potential emissions reductions. Data loggers were used to collect activity data, including hours of use, energy consumption, and charging information over periods from 6 to 21 months. The results showed that the BE forklifts, BE railcar mover, and the eRTG averaged 2-3 hours, 5 hours, and 14 hours of use per day of operation, respectively. The average energy use for
Frederickson, ChasVu, AlexanderMakki, MaedehJohnson, KentDurbin, ThomasBurnette, AndrewHuang, EddyAlvarado, EricaRao, Leela
Hydrogen fuel cell is one of paths to achieve carbon neutrality transportation. In the last two decades, significant improvements have been made in compactness, efficiency and durability of fuel cell systems. For heavy duty truck applications, a life span similar to heavy duty diesel engines is required. As a critical component in the fuel cell system, air compressors play an important role to meet fuel cell systems’ high efficiency and durability requirements. In this paper, a holistic approach has been taken to develop a series of airfoil bearing centrifugal compressors for a wide range of applications from forklift, passenger vehicles to commercial vehicles, and achieve high efficiency and durability of one million start-stops. In the new platform development, cooling circuit was optimized so that the external cooling air circuit for the rotor and air bearings is no longer needed, which resulted in 4% efficiency improvement. Hollow rotor structure was adopted to achieve lightweight
Wang, QianzhenYuan, XixinTao, ZhangFeng, Jin ZengWang, JuanXiao, YongZhou, LeiXin, Jun
Novel experimental and analytical methods were developed with the objective of improving the reliability and repeatability of coast-down test results. The methods were applied to coast-down tests of a SUV and a tractor-trailer combination, for which aerodynamic wind-tunnel data were available for comparison. The rationale was to minimize the number of unknowns in the equation of motion by measuring rolling and mechanical resistances and wheel-axle moments of inertia, which was achieved using novel experimental techniques and conventional rotating-drum tests. This led to new modelling functions for the rolling and mechanical resistances in the equation of motion, which was solved by regression analysis. The resulting aerodynamic drag coefficient was closer to its wind-tunnel counterpart, and the predicted low-speed road load was closer to direct measurements, than the results obtained using conventional methods. It is anticipated that applying the novel techniques to characterize the
Tanguay, Bernardde Souza, Fenella
In recent years, the stronger push for reducing GHG and NOx emissions has challenged vehicle manufacturers globally. In USA, Multi-Pollutant Emissions Standards for Model Years 2027 and Later Light Duty and Medium-Duty Vehicles released by EPA in April 2023 aims to reduce the CO2 emissions by 56% and 44%, respectively, for light and medium duty vehicles by 2032 from 2026 levels. It also includes the NMOG+ NOx standards, which require a 60 – 76% reduction by 2032 from 2026 levels for light to medium-duty vehicles. Europe also aims to reduce CO2 emissions by 55% by 2030 from 1990 levels and 100% by 2035. To achieve such low levels of CO2 emissions, especially in the near-term scenario of limited EV sales, hybridization of conventional powertrains has found renewed interest. While hybrid powertrains add complexity, if optimized well for the application, they can offer best tradeoff between upfront cost, range, payload, performance, emissions and off-ambient operation. This study
Fnu, DhanrajCorreia Garcia, BrunoPaul, SumitJoshi, SatyumFranke, Michael
An energy-use analysis is presented to examine the potential energy-savings and range-extension benefits of aerodynamic improvements to tractors and trailers used in commercial transportation. The impetus for the study was the observation of aerodynamically-redesigned/optimized tractor shapes of emerging zero-emission commercial vehicles that have the potential for significant drag reduction over conventional aerodynamic tractors. Using wind-tunnel test results, a series of aerodynamic performance models were developed representing a range of tractor and trailer combinations. From modern day-cab and sleeper-cab tractors to aerodynamically-optimized zero-emission cab concepts, paired with standard dry-van trailers or low-drag trailer concepts, the study examines the energy use, and potential savings thereof, from implementing various fleet configurations for different operational duty cycles. An energy-use analysis was implemented to estimate the energy-rate contributions associated
McAuliffe, BrianGhorbanishohrat, Faegheh
Introducing hydrogen (H2) into the intake air of diesel engines provides a near-term approach to reducing tailpipe CO2 emissions from heavy-duty commercial vehicles. The premixed hydrogen results in a complex H2-Diesel dual fuel (H2DF) combustion process, where H2 can both participate in the non-premixed diesel combustion and result in a propagating H2/air combustion. These interactions influence engine combustion characteristics, including in-cylinder pressure and heat release rate (HRR), as well as emissions. The nature and extent of the impact depends on the amount of H2 introduced as a function of the total fuel energy (H2 energy share ratio - HES), the trapped air mass, and engine operating conditions. To optimize the HES ratio under different conditions, it is crucial to understand how H2DF combustion differs from diesel combustion and how this limits engine operation and impacts emissions. To investigate these effects, a heavy-duty class 8 truck fitted with an H2DF system
Farzam, RezaGuan, MangGmoser, RaineSteiche, PatrickKirchen, PatrickMcTaggart-Cowan, Gordon
Electrifying truck fleets has the potential to improve energy efficiency and reduce carbon emissions from the freight transportation sector. However, the range limitations and substantial capital costs with current battery technologies imposes constraints that challenge the overall cost feasibility of electrifying fleets for logistics companies. In this paper, we investigate the coupled routing and charge scheduling optimization of a delivery fleet serving a large urban area as one approach to discovering feasible pathways. To this end, we first build an improved energy consumption model for a Class 7-8 electric and diesel truck using a data-driven approach of generating energy consumption data from detailed powertrain simulations on numerous drive cycles. We then conduct several analyses on the impact of battery pack capacity, cost, and electricity prices on the amortized daily total cost of fleet electrification at different penetration levels, considering availability of fast
Wendimagegnehu, Yared TadesseAyalew, BeshahIvanco, AndrejHailemichael, Habtamu
Emerging zero-emission-powertrain concepts are providing opportunities to re-shape heavy trucks for improved aerodynamic performance. To investigate the potential for energy savings through aerodynamic improvements, with a goal to inform operators and regulators of such benefits, a multi-phase project was initiated to design and evaluate aerodynamic improvements for Class 8 tractor-trailer combinations. While the focus was battery-electric and hydrogen-fuel-cell powered trucks, improvements for internal-combustion powered trucks were also examined. Previously-reported activities included a scaled-model wind-tunnel test that demonstrated the potential for up to 9% drag reduction from simple shape adaptations, with a follow-up CFD study providing guidance towards further optimization. This paper presents wind-tunnel-test results using a high-fidelity 30%-scale model of a new aerodynamic tractor concept, with comparison to a conventional North American Class 8 tractor with a modern
Ghorbanishohrat, FaeghehMcAuliffe, BrianO'Reilly, Harrison
Accurate mass estimation is essential for commercial heavy-duty vehicles (HDVs) because fluctuating payloads significantly impact energy consumption. Precise vehicle mass estimates enhance the accuracy of energy consumption models, leading to more effective energy management systems and performance optimization strategies. For example, improved energy estimates can lead to more optimized routing and refueling schedules, improving operational efficiency and reducing costs. For electric HDVs, accurate mass estimates are crucial for battery sizing, range prediction, and optimized charge scheduling. While direct mass measurements may be obtained through external weight-in-motion or specialized onboard weighing systems, this paper focuses on methods that use data from Controller Area Network systems for alternative real-time predictions. The challenge lies in identifying a method that performs well under the highly variable and often sparse data conditions typical of HDV driving datasets
Jayaprakash, BharatEagon, MatthewFakhimi, SetayeshKotz, AndrewNorthrop, William
Effective traffic management and energy-saving techniques are increasingly needed as metropolitan areas grow and traffic volumes rise. This work estimates fuel consumption over three selected routes in an urban context using spatio-temporal modeling essentially building on a previously developed approach in traffic prediction and forecasting. A weighted adjacency matrix for a Graph Neural Network (GNN) is constructed in the original approach which combines graph theory frameworks with travel times obtained from average speeds and distances between traffic count stations. Next, the traffic flow estimate uncertainty is measured using Adaptive Conformal Prediction (ACP) to provide a more reliable forecast. This work predicts fuel consumption under different scenarios by utilizing Monte Carlo simulations based on the expected traffic flows providing insights into energy efficiency and the best routes to take. The study compares passenger vehicles' and heavy-duty trucks' mean fuel
Patil, MayurMoon, JoonHanif, AtharAhmed, Qadeer
Background. In 2022, vulnerable road user (VRU) deaths in the United States increased to their highest level in more than 40 years. At the same time, increasing vehicle size and taller front ends may contribute to larger forward blind zones, but little is known about the role that visual occlusion may play in this trend. Goal. Researchers measured the blind zones of six top-selling light-duty vehicle models (one pickup truck, three SUVs, and two passenger cars) across multiple redesign cycles (1997–2023) to determine whether the blind zones were getting larger. Method. To quantify the blind zones, the markerless method developed by the Insurance Institute for Highway Safety was used to calculate the occluded and visible areas at ground level in the forward 180° arc around the driver at ranges of 10 m and 20 m. Results. In the 10-m forward radius nearest the vehicle, outward visibility declined in all six vehicle models measured across time. The SUV models showed up to a 58% reduction
Epstein, Alexander K.Brodeur, AlyssaDrake, JuwonEnglin, EricFisher, Donald L.Zoepf, StephenMueller, Becky C.Bragg, Haden
Driving speed affects road safety, impacting crash severity and the likelihood of involvement in accidents on highway bridges. However, their impacts remain unclear due to inconsistent topography and consideration of crash types. This study aimed to identify the status of accidents and factors associated with accidents occurring on bridges along the Mugling to Narayanghat highway segment in Nepal. The study area involves the selected highway segment stretching from Aptari junction (CH: 2+42) to Mugling junction (CH: 35+677). Spanning 33.25 km, the road traverses through both hilly and Terai regions. The study employs descriptive and correlation statistics to analyze crash data from 2018 to 2023, aiming to achieve its research objectives. The study reveals overspeeding as the primary cause of crashes, notably head-on and rear-end collisions. Two-wheelers frequently exceed the speed limit of 40 km/h limit (29–88 km/h), and four-wheelers do similarly (18–81 km/h), leading to overspeeding
Giri, Om PrakashShahi, Padma BahadurKunwar, Deepak Bahadur
This SAE Recommended Practice establishes uniform test procedures and performance requirements for the defrosting system of enclosed cab trucks, buses, and multipurpose vehicles. It is limited to a test that can be conducted on uniform test equipment in commercially available laboratory facilities. For laboratory evaluation of defroster systems, current engineering practice prescribes that an ice coating of known thickness be applied to the windshield and left- and right-hand side windows to provide more uniform and repeatable test results, even though - under actual conditions - such a coating would necessarily be scraped off before driving. The test condition, therefore, represents a more severe condition than the actual condition, where the defroster system must merely be capable of maintaining a cleared viewing area. Because of the special nature of the operation of most of these vehicles (where vehicles are generally kept in a garage or warmed up before driving), and since
Truck and Bus Windshield Wipers and Climate Control Comm
This SAE Recommended Practice establishes testing methods and performance requirements for windshield wiping systems on trucks, buses, and multipurpose passenger vehicles with a GVWR of 4500 kg (10000 pounds) or greater and light-duty utility vehicles with a GVWR of less than 4500 kg (10000 pounds). The test procedures and minimum performance requirements outlined in this document are based on currently available engineering data. It is the intent that all portions of the document will be periodically reviewed and revised as additional data regarding windshield wiping system performance are developed.
Truck and Bus Windshield Wipers and Climate Control Comm
The sound generated by electric propulsion systems differs compared to the prevalent sound generated by combustion engines. By exposing listeners to various sound situations, the manufacturer can start understanding which direction to take to achieve compelling battery electric vehicle trucks from a sound perspective. The main objective of this study is to understand what underlying aspects decide the experience and perception of heavy vehicle–related sounds in the context of electrified propulsion. Using a thematic analysis of data collected at a listening experiment conducted in 2020, factors affecting the perception of novel sounds generated by a first-generation electric truck are investigated. A hypothesis is that the experience of driving or being a passenger in electric trucks will affect the rating and response differently compared to listeners not yet experienced with this sound. The results show that the combination of individual preference and experience, hearing function
Nyman, BirgittaFagerlönn, JohanNykänen, Arne
With the rapid development of smart transport and green emission concepts, accurate monitoring and management of vehicle emissions have become the key to achieving low-carbon transport. This study focuses on NOx emissions from transport trucks, which have a significant impact on the environment, and establishes a predictive model for NOx emissions based on the random forest model using actual operational data collected by the remote monitoring platform.The results show that the NOx prediction using the random forest model has excellent performance, with an average R2 of 0.928 and an average MAE of 43.3, demonstrating high accuracy. According to China's National Pollutant Emission Standard, NOx emissions greater than 500 ppm are defined as high emissions. Based on this standard, this paper introduces logistic regression, k-nearest neighbor, support vector machine and random forest model to predict the accuracy of high-emission classification, and the random forest model has the best
Lin, YingxinLi, Tiezhu
The introduction of autonomous truck platoons is expected to result in drastic changes in operational characteristics of freight shipments, which may in turn have significant impacts on efficiency, energy consumption, and infrastructure durability. Since the lateral positions of autonomous trucks traveling consecutively within a lane are fixed and similar (channelized traffic), such platooning operations are likely to accelerate damage accumulation within pavement structures. To further advance the application of truck platooning technology in various pavement environments, this study develops a flexible evaluation method to evaluate the impact of lateral arrangement within autonomous truck platoons on asphalt pavement performance. This method simplifies the impact of intermittent axle load applications along the driving direction within a platoon, supporting platoon controllers in directly evaluating pavement damage for different platoon configurations. Specifically, a truck platoon
Wenlu, YuYe, QinChen, DaoxieMin, YitongChen, Leilei
Overloading of trucks will not only damage road infrastructure, lead to exhaust pollution, and even cause serious traffic accidents, resulting in huge losses of life and property. However, most of the methods to evaluate truck overloading are limited by environmental factors, so it is impossible to monitor truck overloading in real time. In order to solve this problem, a truck overload detection method based on real-time vehicle diagnosis big data is proposed in this paper. The method comprehensively considers multiple factors affecting the actual power of trucks through mathematical modeling. It based on the effects of overload on fuel combustion efficiency, harmful gas emission, exhaust temperature, and vehicle power loss, The truck overload evaluation model is constructed to judge whether the truck is overloaded or not in real time. Based on the truck overload assessment and truck accident risk factor extraction , a real-time operation risk assessment model based on fault tree
Chen, YuguangLin, HonghaoWang, Yanan
The effectiveness of the negative suspension structure (NSS) in isolating the driver’s seat vibrations has been demonstrated based on the seat’s model or vehicle’s one-dimensional dynamic model. To fully assess the effectiveness and stability of the seat’s NSS (S-NSS) on different models of vehicles, the three-dimensional models of the vibratory rollers (VR), heavy trucks (HT), and passenger cars (PC) have been built to assess the effectiveness of S-NSS compared to the seat’s passive suspension (S-PC) and seat’s control suspension (S-CS). The effectiveness of S-NSS is then investigated under all operating conditions of vehicles. The investigation results indicate that under a same simulation condition, S-NSS improves the ride comfort and health of the driver better than both S-PS and S-CS on all VR, HT, and PC. However, the effectiveness of S-NSS on PC is lower than on both VR and HT while the effectiveness of S-CS on PC is better than on both VR and HT. Besides, the effectiveness of S
Su, BeibeiWang, QiangSong, Fengxiang
This SAE Recommended Practice covers the design and application of a 120 VAC single phase engine based auxiliary power unit or GENSET. This document is intended to provide design direction for the single phase nominal 120 VAC as it interfaces within the truck 12 VDC battery and electrical architecture providing power to truck sleeper cab hotel loads so that they may operate with the main propulsion engine turned off.
Truck and Bus Electrical Systems Committee
This SAE Recommended Practice covers passive torque biasing axle and center differentials used in passenger car and light truck applications. Differentials are of the bevel gear, helical gear, and planetary types, although other configurations are possible.
Drivetrain Standards Committee
This SAE Recommended Practice establishes a uniform, powered vehicle test procedure and minimum performance requirement for lane departure warning systems used in highway trucks and buses greater than 4546 kg (10000 pounds) gross vehicle weight (GVW). Systems similar in function but different in scope and complexity, including lane keeping/lane assist and merge assist, are not included in this document. This document does not apply to trailers, dollies, etc. This document does not intend to exclude any particular system or sensor technology. This document will test the functionality of the lane departure warning system (LDWS) (e.g., ability to detect lane presence and ability to detect an unintended lane departure), its ability to indicate LDWS engagement, its ability to indicate LDWS disengagement, and its ability to determine the point at which the LDWS notifies the human machine interface (HMI) or vehicle control system that a lane departure event is detected. Moreover, this
Truck and Bus Automation Safety Committee
There are various steering technologies are available in market nowadays. Hydraulic Power Steering (HPS) is one of them. As hydraulic name is linked to it the temperature role comes to play. While doing hard cornering the hydraulic oil used to assist the working in steering system get over heated, due to which oil loses its viscosity became one of the major causes of hard steer in trucks. Also, due to limited space the large heat exchanger cannot be used there. So, objective of this Thesis is to examine an effective solution which can be compact in design and at the same time should be effective to solve this problem. After going through literature analysis, we finalize that the Principal of Pulsating Heat Pipe could be a possible solution. So, for that we design different model based on previous research work in Creo and simulate them in Star CCM+ to finalize the optimality.
Saikrishna, VNLP, RudreshaYadav, SatyendraB, RuthvikaVishwasa, Viditha
Parallel hybrid commercial vehicles equipped with automated manual transmissions are extensively utilized in the commercial vehicle sector due to their minimal configuration changes, high energy efficiency, and multi-mode driving capabilities. The key to enhancing the fuel economy of these vehicles lies in the mode switching and gear shift control strategy. To meet the driving requirements of these vehicles and optimize their fuel efficiency, this study introduces a mode switching and gear shift control strategy based on dynamic programming for a parallel hybrid commercial vehicle. First, dynamic programming is applied to the energy management strategy of the hybrid electric vehicle to determine the optimal fuel-efficient power output. Subsequently, the results from dynamic programming simulations are utilized to establish the mode switching boundaries and gear shift patterns. An improved mode switching and gear shift control strategy is then proposed and compared with the control
Zhai, XumaoLi, YujuanJiang, GuangzongYan, ZhengfengYao, MingyaoSun, Yansen
Hydrogen fuel cell trucks have enormous development potential in the pursuit of global carbon neutrality and sustainable development. However, their commercialization and mass production are facing challenges in various aspects, especially the durability problem of fuel cells. This paper is intended to set up a high-power hydrogen fuel cell system (FCS) model, considering the fuel cell degradation factors, and based on this, proposes a two-layer fuzzy energy management strategy (EMS) to optimize the life of fuel cell and the total energy consumption of the vehicle. The first control layer provides real-time energy distribution efficiently from multiple sources and thus allows flexibility in energy supply. The second layer regulates the dynamic adjustment of fuel cell output power with degradation of both fuel cells and batteries considered, to make the prolonging of system lifetime possible. In this respect, the equivalent hydrogen consumption, which incorporates fuel cell degradation
Hou, QuanWang, HanZhu, Dan
Predictive Cruise Control (PCC) is a promising approach for improving fuel efficiency and reducing operational costs in heavy trucks. However, its implementation using conventional Nonlinear Model Predictive Control (NMPC) methods is hindered by computational limitations, often restricting the use of long-horizon slope information. This paper addresses these challenges by proposing a neural network-enhanced slope-adaptive NMPC framework. A Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) architecture is employed to integrate long-horizon slope information and dynamically update control parameters, effectively overcoming computational constraints of traditional NMPC. To further enhance efficiency, an automated simulation scheduling system is developed, leveraging Large Language Models (LLMs) and expert knowledge to optimize parameter tuning and streamline data collection, significantly reducing training overhead. Validation on a high-fidelity simulation platform
Han, XiaoSong, KangLv, Qing FangZhang, YiXie, Hui
During the operation of autonomous mining trucks in the process of crushing stones, the GPS signal is lost due to signal blockage by the crushing workshop. Simultaneous Localization and Mapping (SLAM) becomes critical for ensuring accurate vehicle positioning and smooth operation. However, the bumpy road conditions and the scarcity of plane and corner feature points in mining environments pose challenges to SLAM algorithms in practical applications, such as pose jumps and insufficient positioning accuracy. To address this, this paper proposes a high-precision positioning algorithm based on inertial navigation 3D signals, incorporating point cloud motion distortion correction, a vehicle roll model, and an Adaptive Kalman Filter (AKF). The goal is to improve the positioning accuracy and stability of autonomous mining trucks in complex scenarios. This paper utilizes real-world operational data from mining vehicles and adopts a 3D point cloud motion distortion correction algorithm to
Meng, ChunyangSong, KangXie, HuiXing, Wanyong
In cold environments, it is slow and risky for charging rate of electric heavy-duty trucks due to lithium plating. Common heating-charging methods overlook the complex dynamics between current, temperature, and battery aging, which need to be further improved. This study presents a tailored thermal management strategy for low-temperature battery charging, analyzing heating performance and battery improvement effect on the fast-charging performance. The data-driven multi-tiered power heating strategy based on a customer electro-thermal-aging model was proposed to minimize charging time and costs. The heating power combinations have been optimized by a particle swarm optimization algorithm, which outperforms conventional methods that aim to reach a set temperature. The optimized strategy reduced charging time by 11% and battery life degradation by only 0.0512%, enhanced the efficiency of cold-weather fast charging for electric trucks.
Lin, JieweiJiang, FeifanDai, HuweiSun, LeiLiu, BaoguoLi, ShiboZhang, Junhong
The optimization of gear shifting is a critical process in heavy-duty trucks for adjusting engine operating points, enabling a multi-objective balance between power, fuel efficiency, and comfort. However, this process is challenged by the nonlinear characteristics of engine fuel consumption, power interruptions during AMT (Automated Manual Transmission) shifts, and uncertainties in driving conditions. This study proposes a rolling optimization shift strategy for heavy trucks equipped with AMT, based on a multi-scale prediction of internal combustion engine fuel consumption on the road. Firstly, a predictive model for the energy efficiency and dynamics of heavy-duty trucks with AMT was developed, accounting for the engine’s engine’s operating condition points and power interruptions during shifting. Secondly, a future power demand, vehicle speed, and fuel consumption prediction algorithm was designed, iterating based on accelerator pedal position forecasts and dynamic modeling. Finally
Liu, XingyiZhou, QuanyuZhang, LeiboLv, DongxuanSun, XiaopengGao, JinhaoSong, KangXie, Hui
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