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In order to study the influence of engine silicone oil fan clutch on the performances of engine cooling system under different control strategies, a model of engine cooling system for light truck is established. The working characteristics of the silicone oil clutch and the measured performance parameters of the cooling system components are taken into account in our proposed model. Modeling methods for different silicone oil fan control strategies are also given. Using the established model, the performance parameters under different vehicle speeds, such as coolant temperature of engine outlet and power consumption of cooling fan, are calculated and analyzed. The in-suite measurement of the engine cooling system is carried out to get the temperatures of engine coolant inlet and outlet from engine ECU. The model is validated by the comparison between the calculation and the measured results.

Multi-motor powertrain topologies are playing an increasingly important role in the development of heavy duty battery electric trucks due to the changing driving requirements of these vehicles. The use of multiple motors and/or transmissions in a powertrain provides additional degrees of freedom for the energy management. The energy management system (EMS) consist of the gear selection strategy and torque split between the drive motors. The aim of the EMS is thereby to achieve high energy efficiency in motor and regenerative operation, while reducing the number of gear changes to ensure driving comfort. Ongoing research focuses on the energy management system of hybrid electric trucks, where the aim is to optimize the torque split between the combustion engine and the electric motor. In this paper, the EMS for an electric truck is described as a mixed-integer nonlinear control problem. This type of optimal control problem is notoriously difficult to solve.

By installing an automated mechanical transmission (AMT) on heavy-duty vehicles and developing a reasonable shift strategy, it can reduce driver fatigue and eliminate technical differences among drivers, improving vehicle performance. However, after detaching from the experience of good drivers, the current shifting strategy is limited to the vehicle state at the current moment, and cannot make predictive judgment of the road environment ahead, and problems such as cyclic shifting will occur due to insufficient power when driving on the ramp. To improve the adaptability of heavy-duty truck shift strategy to dynamic driving environments, this paper first analyzes the shortcomings of existing traditional heavy-duty truck shift strategies on slopes, and develops a comprehensive performance shift strategy incorporating slope factors. Based on this, forward-looking information is introduced to propose a predictive intelligent shift strategy that balances power and economy.

Heavy commercial vehicles have large variations in load and high centroid positions, so it is particularly important to obtain timely and accurate load information during driving. If the load information can be accurately obtained and the braking force of each axle can be distributed on this basis, the braking performance and safety of the entire vehicle can be improved. Heavy commercial vehicle load information is different from passenger vehicles, so it is particularly important to study commercial vehicles engaged in freight and passenger transportation. Presently, numerous research endeavors focus on evaluating the quality of passenger vehicles. However, heavy commercial vehicles exhibit notable distinctions compared to their passenger counterparts. Due to substantial variations in vehicle mass pre and post-loading, coupled with notable suspension deformations, significant changes are observed.

The transition towards electrification in commercial vehicles has received more attention in recent years. This paper details the conversion of a production Medium-Duty class-5 commercial truck, originally equipped with a gasoline engine and 10-speed automatic transmission, into a battery electric vehicle (BEV). The conversion process involved the removal of the internal combustion engine, transmission, and differential unit, followed by the integration of an ePropulsion system, including a newly developed dual-motor beam axle that propels the rear wheels. Other systems added include an 800V/99 kWh battery pack, advanced silicon carbide (SiC) inverters, an upgraded thermal management system, and a DC fast charging system. A key part of the work was the development of the propulsion system controls, which prioritized drivability, NVH suppression, and energy optimization.

Toyota has developed a new 2.4L L4 turbo (2.4L-T) engine with 8AT and 1-motor hybrid electric powertrains for midsize pickup trucks. The aim of these powertrains is to fulfill both strict fuel economy and emission regulations toward “Carbon Neutrality”, while exceeding customer expectations. The new 2.4L L4 turbocharged gasoline engine complies with severe Tier3 Bin30/LEVIII SULEV30 emission regulations for body-on-frame midsize pickup trucks improving both thermal efficiency and maximum torque. This engine is matched with a newly developed 8-speed automatic transmission with wide range and close step gear ratios and extended lock-up range to fulfill three trade-off performances: powerful driving, NVH and fuel economy. In addition, a 1-motor hybrid electric version is developed with a motor generator and disconnect clutch between the engine and transmission.

The auto industry is one of the major contributors for noise pollution in urban areas. Specifically, highly populated heavy commercial diesel vehicle such as buses, trucks are dominant because of its usage pattern, and capacity. This noise is contributed by various vehicle systems like engine, transmission, exhaust intake, tires etc. When the pass by noise levels exceeds regulatory limit, as per IS 3028, it is important for NVH automotive engineer to identify the sources & their ranking for contribution in pass by noise. The traditional methods of source identification such as windowing technique, sequential swapping of systems and subsystems which are time consuming.Also advanced method in which data acquisition with a synchronizing technology like telemetry or Wi-Fi for source ranking are effective for correctness.However they are time and resource consuming, which can adversely impact product development timeline.

High currents flowing through various traces of a printed circuit boards (PCB) causes thermal run away and PCB warpage due to the occurrence of high heat density. The present study discusses on steady state thermal analysis performed in a PCB kept inside an enclosure. Thermal analysis allows PCB designer to quickly move and confirm the component’s placement by examining the temperature plots predicted on the PCB surface. A PCB particularly designed for automated manual transmission (AMT) application employed in Ashok Leyland electric vehicle (EV) trucks is used for this present study. The performed simulations are preliminary level and carried out with commercially available software Altair Simlab ElectroFlo 2022.3. Simlab is a PCB level EDA (Electronic Design Automation) software suite used for design and analysis, and thus helps in minimizing the development cycles.

The commercial vehicles market is dominated by manual transmission, due to lower ownership cost. Generally, commercial vehicles are used in large numbers by the fleet owners. The transmission endurance life is very important to a vehicle owner. On the other hand, driver fatigue can be reduced with a smooth gear change process. The gear change process in a manual transmission is carried out with the help of the synchronizer pack. The crucial function of a synchronizer pack in an automotive transmission is to match the speed of the target gear for smooth gear shifting. In a transmission, the loose and the weakest part is the synchronizer ring. The failure of the synchronizer affects smooth gear shifting and it also affects the endurance life of the transmission. The synchronizer ring can fail due to poor structural strength, synchronizer liner wear, synchronizer liner burning, etc.

Heavy vehicles are major fuel consumers in road transportation, and the traditional way to reduce fuel consumption is to reduce weight, resistance, improve mechanical transmission efficiency, and improve engine thermal efficiency. However, European heavy-duty truck companies took the lead in realizing predictive cruise control (PCC) technology on the basis of cruise through intelligent network technology, based on ADAS maps, and achieved good fuel saving effects. In this paper, by studying the fuel consumption characteristics of trucks, designing the dynamic parameters of the load and whole vehicle, the predictive adaptive cruise control (PACC) technology is realized based on the predictive cruise strategy, and the statistics of fuel saving rate under different cruise ratio conditions are analyzed through the big data platform.

Estimated engine torque is an important parameter used by automotive systems for automated transmission and clutch control. Heavy-duty engine and transmission manufacturers widely use SAE J -1939 based ECU torque calculation based on mass air/fuel flow steady state maps created during calibration of the engine for this purpose. As an alternative, to enhance the accuracy of this important control variable, a virtual flywheel torque sensor (VFTS) was developed. It measures the engine torque based on the harmonics of the instantaneous flywheel speed signal. Initial dynamometer testing showed the VFTS estimated torque values exhibited a maximum inaccuracy of 12% of the actual measured torque over the range of conditions tested. In this paper we report the results of on road truck testing of the VFTS. A loaded heavy truck with a gross vehicle weight rating of 80,000 pounds was used.

Since there are no typical working conditions in the field of engineering vehicles, this paper implements the construction of driving conditions based on Markov stochastic model and energy management strategy of a multi-mode hybrid mine dump truck based on dynamic programming algorithm under this background. Firstly, on the basis of existing vehicle driving data, we calculate the velocity transfer probability matrix with the Markov stochastic model, and then construct the vehicle driving condition after predicting the velocity. The constructed working conditions are applied to the energy management strategy of dynamic programming algorithm to calculate the energy consumption of the hybrid mining truck. It is proved that this construction method can be applied to the hybrid electric mine dump truck, and the DP based energy management strategy has lower energy consumption.

The fuel economy and emission of the hybrid vehicle depend largely on the selected engine. And the dedicated hybrid engine (DHE) can be controlled to operate in the optimal operating range because DHE can be decoupled from the vehicle transmission system. The main purpose of this paper is to improve the thermal efficiency of the diesel engine under common operating conditions combined with high compression ratio (CR) and early or late intake valve closing (IVC) angle. According to the vehicle road spectrum data, the optimal operating range of the engine is determined to be 1200-1400 rpm and 70%-90% load. Then CR and IVC angle are optimized by using the calibrated one-dimensional thermodynamic model of the engine under limited peak combustion pressure (Pmax). The results show that the adjustment of IVC angle and CR can control the thermal state at the end of compression stroke. The combination of CR and IVC angle can achieve the optimal fuel consumption improvement.

The evaluation of the acceleration, velocity, and travel distance of a motor vehicle is an issue that arises frequently in the analysis of vehicle accidents. It is well known that the acceleration capabilities of a motor vehicle generally reduce as the velocity increases. Vehicle accident reconstruction has traditionally used constant acceleration models with stepped decreases of acceleration as the velocities, distances, and loading increase. For any given vehicle, the energy output of the engine that can be transmitted to the drivetrain remains within a power band of the operating engine. Transmissions efficiently transfer this relatively constant power to the drive wheels. Using the mathematical relationships of the “power equations,” the acceleration, velocity, and travel distances for vehicles can be reasonably evaluated with limited test information. Adjustments for differing load conditions and terrain are readily incorporated into the model.

Electrification is a very current topic for all the mobile machinery whose primary source of power is an internal combustion engine; among those the light weight passenger vehicles represent the first field of application of this trend and also the state of the art of the technology. Agriculture is a huge fuel consumer sector and for this reason the tractor industry is now working on electrification, proposing different approaches for different power sizes: the “Battery Electric Vehicle” topology is proposed for small and mid-power size tractors, while for the big ones various hybrid architectures couple the internal combustion engine to electric units. In this paper a reference tractor is considered, endowed with an input coupled hydro-mechanical Continuously Variable Transmission and an alternative compound architecture is proposed, which provides the same performances and it is more suitable for electrification.

Abstract Lubrication has been a major area of interest in engineering. Especially in vehicle transmissions, lubrication plays a very crucial role because gears and bearings are constantly subjected to heavy loads. Proper lubrication is essential for maintaining system performance and ensuring endurance life. Insufficient lubrication can lead to excessive wear, increased friction, and eventually, failures in the transmission components. However, excess lubrication can result in power losses due to the resistance offered by the excessive lubricant. Therefore, achieving effective lubrication using optimized lubrication system design is vital for ensuring the longevity and efficiency of the transmission system. Majorly, two types of lubrication methods are used in transmissions: splash lubrication and forced lubrication. This article focuses on forced lubrication, where the lubrication system actively delivers the required flow of lubricant to specific locations within the transmission.

The scope of this SAE Standard is the definition of the functional, environmental, and life cycle test requirements for electrically operated backup alarm devices primarily intended for use on off-road, self-propelled work machines as defined by SAE J1116 (limited to categories of (1) construction, and (2) general purpose industrial).

Globally, automotive sector is moving towards improving off-road performance, durability and safety. Need of off-road performance leads to unpredictable overload to powertrain system due to unpaved roads and abuse driving conditions. Generally, shafts and gears in the transmission system are designed to meet infinite life. But, under abuse condition, it undergo overloads in both torsional and bending modes and finally, weak part in the entire system tend to fail first. This paper represents the failure analysis of one such an incident happened in output shaft under abuse test condition. Failure mode was confirmed as torsional overload using Stereo microscope and SEM. Application stress and shear strength of the shaft was calculated and found overstressing was the cause of failure. To avoid recurrence of breakage, improvement options were identified and subjected to static torsional test to quantify the improvement level.