Global Standards Beijing Creation Beijing Foton Daimler Established,Auman GTL Heavy-duty Truck Launched

On February 18,2012,Beijing Foton Daimler Automotive Co.,Ltd.held the inaugural meeting.On the same afternoon,at China’s first world-class digital model factory of Second Auman Factory,Auman

Chinese company launches hydrogen fuel cell heavy-duty truck

Beiben Trucks Group Co.,Ltd.,a Chinese heavy-duty truck producer,has launched a new vehicle powered by 100-kilowatt hydrogen fuel cells.The truck,to be used as a street sweeper,rolled off the production line on Monday in Beiben's plant in the.city of Baotou in north China's Inner Mongolia Autonomous Region.

Real-Time Co-optimization of Gear Shifting and Engine Torque for Predictive Cruise Control of Heavy-Duty Trucks

Fuel consumption is one of the main concerns for heavy-duty trucks.Predictive cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information.In this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty trucks.To minimize fuel consumption,the problem of the PCC is formulated as a nonlinear model predictive control(MPC),in which the upcoming road elevation information is used.Finding the solution of the nonlinear MPC is time consuming;thus,a real-time implementable solver is developed based on Pontryagin’s maximum principle and indirect shooting method.Dynamic programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed solver.Simulation,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed controller.The results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1%deviation for testing roads.Moreover,the proposed co-optimization controller is implementable in a real-truck,and the proposed MPC-based PCC algorithm achieves a fuel-saving rate of 7.9%without compromising the truck’s travel time.

Application of Connected Truck Data to Evaluate Spatiotemporal Impact of Rest Area Closures on Ramp Parking

Ensuring adequate access to truck parking is critical to the safe and efficient movement of freight traffic. There are strict federal guidelines for commercial truck driver rest periods. Rest areas and private truck stops are the only places for the trucks to stop legally and safely. In locations without sufficient parking areas, trucks often park on interstate ramps, which create safety risks for other interstate motorists. Historically, agencies have employed costly and time intensive manual counting methods, camera surveillance, and driver surveys to assess truck parking. Connected truck data, available in near real-time, offers an efficient alternative to practitioners to assess truck parking patterns and identify areas where there may be insufficient safe parking spaces. This paper presents a case study of interstate I-70 in east central Indiana and documents the observed spatiotemporal impacts of a rest area closure on truck parking on nearby interstate ramps. Results showed that there was a 28% increase in parking on ramps during the rest area closure. Analysis also found that ramps closest to the rest area were most impacted by the closure, seeing a rise in truck parking sessions as high as 2.7 times. Parking duration on the ramps during rest area closure also increased drastically. Although it was expected that this would result in increased parking by trucks on adjacent ramps, this before, during, after scenario provided an ideal scenario to evaluate the robustness of these techniques to assess changing parking characteristics of long-haul commercial trucks. The data analytics and visualization tools presented in this study are scalable nationwide and will aid stakeholders in informed data-driven decision making when allocating resources towards improving the nations commercial vehicle parking infrastructure.

Intermodal Competition: Cargo Airships versus Long-Haul Trucking for Perishable Commodities

Intermodal competition changes with changes in technology, economics, and environmental concerns. Trucks and airships are generally considered not to be competitors, but this depends on the distance of haul. The tonne-kilometer cost of trucking rises much more quickly with distance than it does the cost of a cargo airship. At some distance, the two modes are direct substitutes. The costs of the Mexico-Canada refrigerated truck supply chain are compared with the costs of a 100t-lift, electrically-powered airship. The flight characteristics of the Hindenburg Zeppelin are used as a model for a modern cargo airship. The supply chain cost of trucking tomatoes is used to test the theorical proposition. The cost difference works out to about US10￠/kg (5￠/lb) advantage for trucking Mexican tomatoes to Canada. However, this cost disadvantage of the airship could be made up by their vibrationless ride, better air circulation and one-day service versus four days by truck. This alternative form of transportation could have a positive impact on worldwide north-south distribution of food. Airships can overcome trade barriers and distance to open new markets for perishable food exports. In addition, they would reduce the carbon emissions of transport. Canada imports 160,000 refrigerated truckloads of fruits and vegetables by from the southern US and Mexico. With an average driving distance of 3,000 km, these trucks emit 606,000 MT of CO2 annually. Airships powered by hydrogen fuel cells would have zero-carbon emissions. Markets are not yet incorporating the environmental advantage of airships in any freight comparison, but inevitably this will be important.

Excessive Drowsiness among Truck Drivers in Benin in 2023: Associated Factors and Risk of Crashes Occurrence

Introduction: Over-drowsiness is a condition with serious consequences, including road accidents. The condition, however, is often ignored both by carers as well as victims themselves. The aim of the present study was to investigate the factors associated with excessive drowsiness in Cotonou, Benin 2023, along with its influence on the occurrence of crashes among truck drivers. Methods: This was a descriptive and analytical cross-sectional study, held from March 13 to April 10, 2023, focusing on large truck drivers over 18 years of age, selected by convenience from parking lots in and around the city of Cotonou. Data collected using questionnaires on socio-demographic and behavioral factors, sleeping habits and working conditions were processed using Stata 15.0 software. Excessive drowsiness was defined by a score above 10 on the Epworth scale. Associated factors were found by multiple logistic regression, at a threshold of 0.05. Results: Altogether 304 drivers, all male and aged 35.98 ± 8.42 years, were surveyed. The prevalence of excessive drowsiness was 29.2%. The associated factors identified were not practicing sport OR = 2.27, CI95% = [1.33;3.86], p = 0,002;sleep duration per working day OR = 1.82;CI95% = [1.06;3.11], p = 0,027 and average distance travelled per day OR = 3.40;CI95% = [1.53;7.56], p = 0,003. Excessive drowsiness was associated with a 1.73-fold increased risk of road accidents (CI95% [1.04;2.87];p = 0.03). Conclusion: Communicating excessive drowsiness and its associated factors to all the stakeholders in the haulage chain is essential to help prevent road accidents.

A comparative study on kinetics and dynamics of two dump truck lifting mechanisms using MATLAB simscape

In this paper,two lifting mechanism models with opposing placements,which use the same hydraulic hoist model and have the same angle of 50°,have been developed.The mechanical and hydraulic simulation models are established using MATLAB Simscape to analyze their kinetics and dynamics in the lifting and holding stages.The simulation findings are compared to the analytical calculation results in the steady state,and both methods show good agreement.In the early lifting stage,Model 1 produces greater force and discharges goods in the container faster than Model 2.Meanwhile,Model 2 reaches a higher force and ejects goods from the container cleaner than its counterpart at the end lifting stage.The established simulation models can consider the effects of dynamic loads due to inertial moments and forces generated during the system operation.It is crucial in studying,designing,and optimizing the structure of hydraulic-mechanical systems.

Quantifying the Impact of In-Cab Alerts on Truck Speed Reductions in Ohio

In-cab alerts warn commercial vehicle drivers of upcoming roadway incidents, slowdowns and work zone construction activities. This paper reports on a study evaluating the driver response to in-cab alerts in Ohio. Driver response was evaluated by measuring the statistical trends of vehicle speeds after the in-cab alerts were received. Vehicle speeds pre and post in-cab alert were collected over a 47 day period in the fall of 2023 for trucks traveling on interstate roadways in Ohio. Results show that approximately 22% of drivers receiving Dangerous Slowdown alerts had reduced their speeds by at least 5 mph 30 seconds after receiving such an alert. Segmenting this analysis by speed found that of vehicles traveling at or above 70 mph at the time of alerting, 26% reduced speeds by at least 5 mph. These speed reductions suggest drivers taking actional measures after receiving alerts. Future studies will involve further analysis on the impact of the types of alerts shown, roadway characteristics and overall traffic conditions on truck speeds passing through work zones.

Seroprevalence Survey of HIV and Hepatitis B Virus and Behavioral Characteristics among Heavy Truck Drivers along Port Sudan-Khartoum Highways

The prevalence of human immunodeficiency virus (AIDS) and hepatitis B virus among heavy truck drivers and their assistants has been well documented globally in correlation with their behavioral characteristics. The present study aimed to screen for human immunodeficiency virus (HIV), hepatitis B virus (HBV), and behavioral characteristics among heavy truck drivers in Port Sudan. A cross-sectional study was conducted on 274 heavy truck drivers and their assistants who used the highway Port Sudan-Khartoum in Port Sudan city during 2019-2021. Data on behavioral characteristics and substance use habits were collected using a structured questionnaire, and an ELISA test was used to screen for HIV and HBV infections in the study participants. The chi-square test, odds ratio, and confidence intervals were used to find the association between behavioral characteristics and seropositive HIV/HBV. Of the 274 enrolled participants, the seroprevalence rates of HIV were 2.7% and HBV was 23.7%. Ninety-four (34.3%) of them had a history of high-risk sexual behavior outside of marriage;only two (0.7%) used condoms;14.2% of participants reported alcohol use;and 1.1% reported drug use. Univariate analysis revealed that having a sex history outside of marriage with ≥1 sex partner and never using a condom with a spouse or casual partner were significant risk factors for HIV and HBV among drivers. Fortunately, we found that most of the drivers reported low alcohol and drug use. Concerning this study, the seroprevalence of HIV and HBV is highly associated with a history of having sex outside of marriage and sexual behavior among truck drivers and assistances. Additional studies are needed to further investigate other STIs and behavioral characteristics associated with factors in truck drivers/assistance in different truck stop regions in Sudan.

A Predictive Energy Management Strategies for Mining Dump Trucks

The plug-in hybrid vehicles(PHEV)technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks.Meanwhile,plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies(EMS).Therefore,a series hybrid system is constructed based on a 100-ton mining dump truck in this paper.And inspired by the dynamic programming(DP)algorithm,a predictive equivalent consumption minimization strategy(P-ECMS)based on the DP optimization result is proposed.Based on the optimal control manifold and the SOC reference trajectory obtained by the DP algorithm,the P-ECMS strategy performs real-time stage parameter optimization to obtain the optimal equivalent factor(EF).Finally,applying the equivalent consumption minimization strategy(ECMS)realizes real-time control.The simulation results show that the equivalent fuel consumption of the P-ECMS strategy under the experimentally collected mining cycle conditions is 150.8 L/100 km,which is 10.9%less than that of the common CDCS strategy(169.3 L/100 km),and achieves 99.47%of the fuel saving effect of the DP strategy(150 L/100 km).

Numerical simulation of the aerodynamic characteristics of heavy-duty trucks through viaduct in crosswind

In our numerical simulation the hybrid mesh and the SST k-ω turbulence model are adopted to investigate the variations of the aerodynamic loads and the flow field of heavy-duty trucks while crossing a viaduct with 1.1 m high fences in a crosswind at a velocity of 20 m/s. The results show that, with the protection of a fence, the side force is weakened, and the rolling and yaw moments are strengthened while the truck is crossing the viaduct, which relatively reduces the roll-over safety and the driving stability of the truck. Meanwhile, the direction of the side force changes when the truck enters the viaduct, which makes the roll-over safety and the driving stability the lowest during the process.

基于TruckSim矿用汽车转向工况侧倾运动特性分析

车辆发生转向时,由于离心力的作用而产生侧倾运动,空载高速转向时该部分作用将更为明显,进而影响车辆平稳运输。根据悬挂系统的特性差异,对所研究矿用汽车前后悬挂的侧倾中心和侧倾轴进行分析;基于以上分析,对转向时的侧倾运动进行分析,获取关键参数的变化模型;根据理论分析结果,基于Matlab/Simulink建立车辆转向工况表征侧倾运动的分析模型;根据悬挂特性和转向特性,分别建立分析模型,与车辆多体动力学模型联合,基于TruckSim建立整车转向特征分析模型;分析在固定转向盘稳态回转试验时,车辆的行驶轨迹;对空载高速转向工况下,车辆内外轮转角特征曲线,悬挂刚度、位移、侧倾刚度等参数变化进行分析;对比分析考虑转向侧倾与否的转角特征及偏差与理论分析之间的差异,以验证分析的可靠性。结果可知:车辆内外侧悬挂缸出现伸缩跳动,此时出现了附加转向效应叠加在车轮上;车轮需要较大的侧偏角,满足侧向力的需要;此时,整车的转向角关系不单单满足Ackerman定理,还增加了轮胎的侧偏角;未考虑转向侧倾时,转角偏差值随着转角的增加而不断增大,最大偏差达到了0.4223°,而考虑时,转角偏差的目标值为0.3618°。因此表明,所建立的分析模型具有较好的分析结果,能够更精确的反应车辆转向过程中,侧倾运动各部分参数的变化,为此类研究提供参考。

Optimization of Engine Control Strategies for Low Fuel Consumption in Heavy-Duty Commercial Vehicles

The reduction of fuel consumption in engines is always considered of vital importance.Along these lines,in this work,this goal was attained by optimizing the heavy-duty commercial vehicle engine control strategy.More specifically,at first,a general first principles model for heavy-duty commercial vehicles and a transient fuel consumptionmodel for heavy-duty commercial vehicles were developed and the parameters were adjusted to fit the empirical data.The accuracy of the proposed modelwas demonstrated fromthe stage and the final results.Next,the control optimization problem resulting in low fuel consumption in heavy commercial vehicles was described,with minimal fuel usage as the optimization goal and throttle opening as the control variable.Then,a time-continuous engine management approach was assessed.Next,the factors that influence low fuel consumption in heavy-duty commercial vehicles were systematically examined.To reduce the computing complexity,the control strategies related to the time constraints of the engine were parametrized using three different methods.The most effective solution was obtained by applying a global optimization strategy because the constrained optimization problem was nonlinear.Finally,the effectiveness of the low-fuel consumption engine control strategy was demonstrated by comparing the simulated and field test results.

A Comparative Study on the Truck Frame Stiffness with Solid and Beam Element FEA Models

Truck frames should be designed and fabricated with enough rigidity to avoid excessive deflections. Finite element analysis (FEA) plays an important role in all stages of frame designs. While being accurate, 3D solid element FEA models are built upon frame configuration details which are not feasible in the preliminary design stage, partially because of limited available design data of frames and heavy computation costs. This research develops 1D beam element FEA models for simulating frame structures. In this paper, the CAD model of a truck frame is first created. The solid element FEA analysis, which is adopted as the baseline in this study, is subsequently conducted for the stiffness of the frame, Next, beam element FEA analysis is performed for validating the feasibility of the beam element FEA model by comparing the results from the solid and beam element FEA models. It is found that the beam element FEA model can predict the frame stiffness with acceptable accuracy and reduce the computation cost significantly.

Cycle Time Analysis of Open Pit Mining Dump Trucks

This study demonstrates a practical cycle time analysis of dump truck haulage system of “Ukhaa Khudag” open-pit coal mine located in Umnugobi Province, Mongolia. It examines the possibility of minimizing the cycle time of the haulage system as well as factors impacting the speed of the dump truck. The current study divides the open pit mine road for the dump trucks into five sections which are bench road, ramp, surface road, dump road uphill, and dump road. Meanwhile, it investigates the influence of the length, the grade, and the rolling resistance of the road section on the cycle time. The data is analyzed using mathematical regression methods via Microsoft Excel program. For each of the five road sections, we compare the statistical calculations of three regression models: linear, quadratic and exponential;thus, a total of thirty regression models are obtained in this research. Accordingly, the cycle time for each road section is predicted by the most accountable model. The loaded and empty direction of the movement is measured and calculated for each road section, and it appears that the difference between the calculated mean value and the actual cycle time of the models is 0.82 seconds with a relative error of 2.51 percent.

Design and Optimization of New Smoke Exhaust Pipe for Mining Trucks

In order to improve the maintenance efficiency,extend the use time,ensure that the exhaust emission meets the standard,forthe 830E truck heating bucket exhaust pipe design defects,the current single smoke exhaust system is transformed into atime period,convertible smoke exhaust system.After the transformation,it can not only realize the side row to prevent direct corrosion of the box bucket in summer,but also realize the heating of the box bucket at low temperature in winter to prevent snow and ice and frozen blocks from sticking to the box bucket and the materials transported.After the transformation can save a lot of manpower,material resources,financial resources,improve the service life.

一种基于曲率和B样条的矿区装载车辆连续路径规划方法

矿区装载车辆的任务是从进入点到装载点进行装载,然后离开矿区。在进入装载点前,车辆要在回转点改变行进方向,以便倒车进入装载点。针对装载车辆的任务特点,本文提出了一种基于曲率和B样条的路径规划方法。首先,基于车辆运动模型设计了A*算法的成本函数,获得了与车辆转弯半径相关的离散路径。为了进一步获得装载车辆的连续路径,又提出了改进的B样条插值法,使得连续路径两端切线符合车辆起始点和终点的位姿。随后,基于模拟退火算法,获得了车辆的回转点,使得车辆可以在进入装载点前改变前进方向。仿真结果表明,所提出的连续路径规划方法能够保证生成曲率连续的装载车辆路径,并保证路径两端符合车辆在起始点和终点的位姿,为矿区装载车辆的自动驾驶技术提供了基础。

基于多特征融合的露天矿区道路负障碍检测

随着智慧矿山概念的逐步落实,智能化、无人化逐渐在矿区落实,露天矿卡车无人驾驶日益成为矿山智能化建设的主要内容,为解决露天矿区复杂多变的道路因坑洼、塌陷等路面小部分下陷出现的非规则负障碍而导致矿区无人车、重载卡车侧翻等安全难题,提升矿区安全驾驶系数,提出一种多特征融合的露天矿区道路负障碍检测方法。该方法使用BiFPN特征融合模块,提高小型负障碍检测权重占比;引入空间和通道双注意力机制提高对负障碍边缘的特征提取和特征融合能力,从而提高对道路小尺度负障碍的检测精度;采用SIoU Loss作为模型边界框损失函数并使用K-means++方法优化Anchor以提高负障碍检测模型的收敛速度和边界框定位效果,并基于遗传算法优化超参数让模型更贴合矿区场景,最终实现对矿区道路负障碍的快速精准识别。实验表明该检测模型能快速准确识别复杂背景下露天矿区道路负障碍目标,对道路负障碍目标的检测精度、召回率、平均精确度均值分别达到了96.9%、89.9%、95.3%,且该模型大小仅有12.7 MB。对比其他主流检测网络,该网络模型更适合复杂环境下露天矿区非结构化道路行驶安全需求,且该检测模型的鲁棒性好,可适配于多种情况的露天矿区,为实际环境复杂多变的露天矿区非结构化道路负向障碍检测提供了可行的方法,为露天矿无人卡车安全生产运输提供安全预警。

重卡传动轴用高强7075铝合金热流变行为及径向锻造微观组织演变

为研究重型卡车轻量化传动轴用高强7075铝合金在径向锻造时的热变形行为,将大直径7075铝合金挤压棒料预热退火后,取样进行了不同变形条件下的等温压缩试验。分别考虑温度与应变速率对应变强化及软化的影响,构建了适用于中大型7075铝合金传动轴热加工的改进Hansel-Spittel本构模型。根据动态材料模型理论获得了7075铝合金的热加工图,并据此分析了7075铝合金棒料在典型径向锻造工艺中的组织变化。研究结果表明:改进Hansel-Spittel模型能更准确地模拟预热退火态7075铝合金的峰值和稳态流变应力,预测值与试验值的平均相对误差仅为2.71%;7075铝合金在温度为350~450℃、应变速率为0.01~10 s^(-1)范围内具有较高的热加工稳定性,高温及低应变速率的变形条件有利于材料的微观组织演化;预热退火态7075铝合金棒料在经过截面收缩率为55.6%的径向锻造工艺和T6热处理后,原始板条晶粒转变为细化大转角晶粒组织,抗拉强度提高至651 MPa,延伸率提高至12.5%,综合性能得到显著改善。

基于车联网大数据的重型货车载重估计方法

针对当前货车载重计算方法普遍存在的成本高昂及泛化性能不明确的问题,提出一种创新的重型货车载重估计方法,方法融合了车辆行驶动力学理论与机器学习算法,通过有监督学习,利用高速通行大数据对模型进行训练与验证.首先采用聚类分析,确定车辆空、半、满载判断阈值,为后续的计算提供了重要依据.随后,利用随机森林算法训练分类模型,用以判断车辆在一段行驶过程中的基本载重情况.在此基础上,进一步在车辆行驶数据中筛选出稳定行驶的小片段,根据车辆系统动力学理论,对这些小片段车重进行计算.最后,根据载重状态的判断结果,对小片段车重结果进行筛选与计算,得到最终车辆载重计算结果.研究表明,在高速通行大数据的验证下,该方法对于空载及满载状态下趟次车重计算结果的整体平均绝对百分比误差(mean absolute percent error,MAPE)均可控制在10%以内,展现了较高的准确性.相比于现有技术,由于该方法无需安装额外传感器,对数据采集、存储、运算设备的要求也相对较低,因此在成本方面具有显著优势.在交通监管、物流运输、基于大数据的产品开发方面具有快速广泛推广的潜力.