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.

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).

Reducing Electrical Consumption in Stationary Long-Haul Trucks

On average, long-haul trucks in the U.S. use approximately 667 million gallons of fuel each year just for idling. This idling primarily facilitates climate control operations during driver rest periods. To mitigate this, our study explored ways to diminish the electrical consumption of climate control systems in class 8 trucks through innovative load reduction technologies. We utilized the CoolCalc software, developed by the National Renewable Energy Laboratory (NREL), which integrates heat transfer principles with extensive weather data from across the U.S. to mimic the environmental conditions trucks face year-round. The analysis of the CoolCalc simulations was performed using MATLAB. We assessed the impact of various technologies, including white paint, advanced curtains, and Thinsulate insulation on reducing electrical demand compared to standard conditions. Our findings indicate that trucks operating in the eastern U.S. could see electrical load reductions of up to 40%, while those in the western regions could achieve reductions as high as 55%. Such significant decreases in energy consumption mean that a 10 kWh battery system could sufficiently manage the HVAC needs of these trucks throughout the year without idling. Given that many long-haul trucks are equipped with battery systems of around 800 Ah (9.6 kWh), implementing these advanced technologies could substantially curtail the necessity for idling to power air conditioning systems.

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。

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.

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.

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.

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.

Solution to the Horizontal Crossing Problem of Transportation System at Key Points in Open-Pit Mines

In order to reduce the horizontal crossing transportation problems between coal trucks and stripping trucks,large and small vehicles,and transport trucks and belt conveyors at key points of open pit mine in production,the separate transportation mode of underpass bridge and overpass steel trestle is proposed to optimize the open pit development transportation system,so as to solve the practical problems that the horizontal cross of transport vehicles causes vehicle blockage,affects production schedule and production safety.The results show that the horizontal crossing road can be changed into a separate type of overpass steel trestle,which can realize the classified transportation of large and small vehicles,reduce the traffic density,make vehicles with different functions go their own way,eliminate the hidden danger of traffic accidents,and improve the production efficiency.

Using deep neural networks coupled with principal component analysis for ore production forecasting at open-pit mines

Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challenging when training data(e.g.truck haulage information and weather conditions)are massive.In machine learning(ML)algorithms,deep neural network(DNN)is a superior method for processing nonlinear and massive data by adjusting the amount of neurons and hidden layers.This study adopted DNN to forecast ore production using truck haulage information and weather conditions at open-pit mines as training data.Before the prediction models were built,principal component analysis(PCA)was employed to reduce the data dimensionality and eliminate the multicollinearity among highly correlated input variables.To verify the superiority of DNN,three ANNs containing only one hidden layer and six traditional ML models were established as benchmark models.The DNN model with multiple hidden layers performed better than the ANN models with a single hidden layer.The DNN model outperformed the extensively applied benchmark models in predicting ore production.This can provide engineers and researchers with an accurate method to forecast ore production,which helps make sound budgetary decisions and mine planning at open-pit mines.

基于TruckSim的半挂汽车列车转向特性的仿真分析

通过TruckSim软件建立半挂汽车列车整车仿真模型,分别改变半挂汽车列车参数对车辆进行稳态回转仿真试验,以研究不同结构参数对半挂汽车列车转向特性的影响。结果表明:适当的增加牵引车的质量、加长牵引车轴距、加长挂车车轴距牵引车前轴距离、降低挂车质量、缩短牵引车铰接点到前轴的距离,会增加不足转向特性的趋势。

应用TruckSim自卸车操纵稳定性在环仿真平台研究

自卸车良好的操纵稳定性既保证整车正常运行,也保证矿山正常生产运营。根据自卸车整车结构特点和设计参数,基于TruckSim搭建所研究自卸车整车动力学模型,包括电传动系统、悬架系统、转向系统和轮胎等。将悬架系统K&C特性作为整车模型唯一可变输入。基于动力学模型进行操纵稳定性开环仿真,包括方向盘角阶跃、角脉冲和稳态回转仿真。基于TruckSim整车模型,结合PXI实时硬件和Labview搭建整车操纵稳定性驾驶员在环仿真平台,对整车进行双移线工况下闭环试验,对整车操纵稳定性进行分析。分析结果表明:总体上能够很好响应驾驶员操纵并沿着目标路径行驶,且转向轻便;但行驶路径与期望路径存在一定差异,驾驶员需要多次调整转向盘转角才能完成双移线;研究内容和研究结论为进一步实车测试提供参考依据。

基于Trucksim的整车动力性能仿真分析

利用Trucksim软件对某重型商用车进行建模及动力性能仿真,将仿真结果与理论计算值进行比较和分析。结果表明,采用Trucksim建模仿真得到的动力性指标结果均比理论计算结果更加准确。

基于Trucksim的半挂汽车列车方向盘角阶跃输入工况仿真试验研究

通过Truck Sim软件建立半挂汽车列车整车仿真模型,进行方向盘角阶跃输入仿真试验,通过改变牵引车及挂车的参数,以研究不同参数对操纵稳定性的影响.试验表明:适当的增加牵引车的质量、加长牵引车轴距、加长挂车车轴距牵引车前轴的距离,降低挂车质量、缩短牵引车铰接点到前轮的距离能有效提高半挂汽车列车操纵稳定性.

Optimization model of truck flow at open-pit mines and standards for feasibility test

In order to increase production efficiency at open-pit mines, on the basis oflinear programming, a practical mathematical model for optimizing truck flow was developed, whichimproved the traditional fixed manual schedule method. The model has advantages from linearprogramming and objective programming, makes most handling points working at full capacity and keepsan optimized ratio between trucks and excavators. For ensuring feasibility of the model inpractical production, four standards for feasibility test were proposed. The model satisfied all thestandards. The application in a large scale open-pit iron mine indicated that the model reduced thenumber of required trucks by 10 percent compared with the fixed manual schedule method.

Availability-based simulation and optimization modeling framework for open-pit mine truck allocation under dynamic constraints

We present a novel system productivity simulation and optimization modeling framework in which equipment availability is a variable in the expected productivity function of the system. The framework is used for allocating trucks by route according to their operating performances in a truck-shovel system of an open-pit mine, so as to maximize the overall productivity of the fleet. We implement the framework in an originally designed and specifically developed simulator-optimizer software tool. We make an application on a real open-pit mine case study taking into account the stochasticity of the equipment behavior and environment. The total system production values obtained with and without considering the equipment reliability, availability and maintainability (RAM) characteristics are compared. We show that by taking into account the truck and shovel RAM aspects, we can maximize the total production of the system and obtain specific information on the production availability and productivity of its components.