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Abstract The escalating demand for more efficient and sustainable working machines has pushed manufacturers toward adopting electric hybrid technology. Electric powertrains promise significant fuel savings, which are highly dependent on the nature of the duty cycle of the machine. In this study, experimental data measured from a wheel loader in a short-loading Y-cycle is used to exercise a developed mathematical model of a series electric hybrid wheel loader. The efficiency and energy consumption of the studied architecture are analyzed and compared to the consumption of the measured conventional machine that uses a diesel engine and a hydrostatic transmission. The results show at least 30% reduction in fuel consumption by using the proposed series electric hybrid powertrain, the diesel engine rotational speed is steady, and the transient loads are mitigated by the electric powertrain.

SAE J3078 provides test methods and criteria for the evaluation of the operator enclosure environment in earth-moving machinery as defined in ISO 6165. SAE J3078/1 gives the terms and definitions which are used in other parts of SAE J3078. It is applicable to Off-Road Self-Propelled Work Machines as defined in SAE J1116 and tractors and machinery for agriculture and forestry as defined in ANSI/ASAE S390.

The current focus in the ongoing development of autonomous driving systems (ADS) for heavy duty vehicles is that of vehicle operational safety. To this end, developers and researchers alike are working towards a complete understanding of the operating environments and conditions that autonomous vehicles are subject to during their mission. This understanding is critical to the testing and validation phases of the development of autonomous vehicles and allows for the identification of both the nominal and edge case scenarios encountered by these systems. Previous work by the authors saw the development of a comprehensive scenario generation framework to identify an operating domain specification (ODS), or external and internal conditions an autonomous driving system can expect to encounter on its mission to form critical scenario groups for autonomous vehicle testing and validating using statistical patterns, clustering, and correlation.

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.

Building upon prior research, this paper compares computer simulations to a previously conducted rollover crash test of a tractor-semitrailer. The effects of torsional stiffness were elucidated during the correlation of simulations to the rollover test. A commercially available vehicle dynamics and reconstruction software was used for the simulation. Unique aspects of the rollover crash test were modeled in the simulation. A tractor-semitrailer quarter-turn rollover crash test conducted by IMMI was reconstructed using impact and vehicle dynamics models within the simulation software HVE (Human, Vehicle & Environment). The SIMON (SImulation MOdel Non-linear) module and the DyMESH (Dynamic MEchanical SHell) module within HVE were used. During the IMMI test, onboard instrumentation recorded acceleration and roll rate data in six degrees of freedom to characterize both tractor and semitrailer dynamics before and during the rollover event.

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.

Dust testing of vehicles on unpaved roads is crucial in the development process for automotive manufacturers. These tests aim to ensure the functionality of locking systems in dusty conditions, minimize dust concentration inside the vehicle, and enhance customer comfort by preventing dust accumulation on the car body. Additionally, deposition on safety-critical parts, such as windshields and sensors, can pose threats to driver vision and autonomous driving capabilities. Currently, dust tests are primarily conducted experimentally at proving grounds. In order to gain early insights and reduce the need for costly physical tests, numerical simulations are becoming a promising alternative. Although simulations of vehicle contamination by dry dust have been studied in the past, they have often lacked detailed models for tire dust resuspension. In addition, few publications address the specifics of dust deposition on vehicles, especially in areas such as door gaps and locks.

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.

The commercial vehicle sector (especially trucks) has major role in economic growth of a nation. With improving infrastructure, increasing number of commercial vehicles and growing amount of Vulnerable Road Users (VRUs) on roads, accidents are also increasing. As per RASSI (Road Accident Sampling System India) FY2016-21 database, commercial vehicles are involved in 43% of total accidents on Indian roads. One of the major causes of these accidents is Driver Drowsiness and Inattention (DDI) (approx. 10% contribution in total accidents). This paper describes novel driver-in-loop performance assessment methodology for comprehensive verification of Driver Monitoring System (DMS) for commercial vehicle application. Novelty lies in specification of test subjects, driving styles and variety of road traffic scenarios for verification of DMS system. Test setup is made modular to cater to different platform environments (Heavy, Intermediate, Light) with minor modifications.

In the modern and fast growing automotive sector, reliability & durability are two terms of utmost importance along with weight & cost optimization. Therefore it is important to explore new technology which has less weight, low manufacturing cost and better strength. The new technology developed always seek for a quick, cost effective and reliable methodology for its design validation so that any modification can be made by identifying the failures. This paper presents the rig level test methodology to validate and to correlate the CAE derived strain levels, life cycle & failure mode of newly developed light weight stabilizer link for EV Bus suspension

In automotive industry, testing and validation teams are highly dependent on availability of prototype vehicles for testing and evaluation of ride & comfort behavior of vehicles. Special test tracks surfaces are also used (namely Tar road, Express way and driving over a Cleat) to evaluate the ride & comfort through subjective evaluation. Ride is largely affected by transmissibility of road excitations to the driver and other occupant’s seats, influence of suspension, bushes and tire are the major contributors in the transfer path of vibrations. A configurable 1–D simulation model of a Two Axle Truck is developed for quick evaluation of the ride & comfort behavior which is need of the hour for the testing team in optimizing the number of iterations in physical testing. These simulations will help in understanding the ride & comfort behavior and its sensitivity to changes in the component’s characteristics in absence of physical test vehicles.

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.

Commercial transportation is the key pillar of any growing economy. Light and Small commercial vehicles are increasing every day to cater the logistics demand, but there is always a gap between customer’s actual and desired operational efficiency. This is because of lack of organized fleet and efficient fleet operation. The major requirement of fleet owners is timely delivery, high productivity, downtime reduction, real time tracking, etc., Automakers are now providing fleet management application in modern LCV & SCV to satisfy the fleet operator requirement. However, any feature malfunction, consignment mismatch, wrong notification, missed alerts, etc., can incur huge loss to fleet operator and disrupt the entire supply chain. Hence it is very critical to extensively validate the telematics features in fleet management application. This paper explains the approach for exhaustive validation strategy of fleet management applications (B2B) from end user perspective.

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.