Search Results

On the path to decarbonizing road transport, electric commercial vehicles will play a significant role. The first applications were directed to the smaller trucks for distribution traffic with relatively moderate driving and range requirements, but meanwhile, the first generation of a complete portfolio of truck sizes is developed and available on the market. In these early applications, many compromises were accepted to overcome component availability, but meanwhile, the supply chain can address the specific needs of electric trucks. With that, the optimization towards higher usability and lower costs can be moved to the next level. Especially for long-haul trucks, efficiency is a driving factor for the total costs of ownership. Besides the propulsion system, all other systems must be optimized for higher efficiency. This includes thermal management since the thermal management components consume energy and have a direct impact on the driving range.

Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.

Range anxiety in current battery electric vehicles is a challenging problem, especially for commercial vehicles with heavy payloads. Therefore, the development of electrified propulsion systems with multiple power sources, such as fuel cells, is an active area of research. Optimal speed planning and energy management, referred to as eco-driving, can substantially reduce the energy consumption of commercial vehicles, regardless of the powertrain architecture. Eco-driving controllers can leverage look-ahead route information such as road grade, speed limits, and signalized intersections to perform velocity profile smoothing, resulting in reduced energy consumption. This study presents a comprehensive analysis of the performance of an eco-driving controller for fuel cell electric trucks in a real-world scenario, considering a route from a distribution center to the associated supermarket.

Nowadays, Bismuth (Bi) is being applied as an overlay material for engine bearings instead of Lead (Pb) which is an environmentally harmful material. Bi overlay has already been a solid performer in some automotive engine sectors due to its superior load carrying capacity and good robustness characteristic which are necessary to maintain its longevity during the lifetime of engines. The replacement is also seen on relatively larger size engines, such as Trucks and Off-highway heavy duty applications. Basically, these applications require higher power output than passenger cars, and the expected component lifecycle becomes longer. Though Bi has similar material characteristic to traditional Pb, it becomes challenging for the material alone to satisfy these requirements. Polymer overlay is known for its superior anti-wear performance and longer lifetime due to less adhesion against a steel counterpart than metallic materials (included Bi).

To improve the braking energy recovery rate of pure electric garbage removal vehicles and ensure the braking effect of garbage removal vehicles, a strategy using particle swarm algorithm to optimize the regenerative braking fuzzy control of garbage removal vehicles is proposed. A multi-section front and rear wheel braking force distribution curve is designed considering the braking effect and braking energy recovery. A hierarchical regenerative braking fuzzy control strategy is established based on the braking force and braking intensity required by the vehicle. The first layer is based on the braking force required by the vehicle, based on the front and rear axle braking force distribution plan, and uses fuzzy controllers.

Lithium-ion batteries serve as the main power source for contemporary electric vehicles. Safeguarding these batteries against damage is paramount, as it can trigger accelerated performance deterioration, potential fire hazards, environmental threats, and more. This study explores damage progression of a commercial vehicle lithium-ion battery module containing prismatic cells under indentation crush loading. We employed computational simulations of mechanical loading tests to investigate this behavior. Physical tests involved subjecting modules to low-speed (0.05 m/s) indentations using a V-shaped stainless-steel wedge, under six unique loading conditions. During the tests, force, and voltage change with wedge displacement were monitored. Utilizing experimental insights, we constructed a finite element model, which included key components of the battery module, such as the prismatic cells, steel frames, and various plastic parts.

Wrap around distance (WAD) is an important index to evaluate the contact position between pedestrian head and vehicle, and is also one of the key parameters of pedestrian accident reconstruction. The purpose of this paper is to explore whether the pedestrian headform testcan reflect the distribution of head injury in the real world. Firstly, in order to study the distribution of pedestrian head WAD in road accidents in China, a head WAD prediction model was established using logistic regression based on pedestrian height and vehicle collision speed. Secondly, in order to study the distribution of the risk of severe head injuries among pedestrians in accidents, the frequency of pedestrian head impact and the proportion of pedestrian head injury were counted respectively for sedans and SUVs. Subsequently, a risk curve for severe head injuries was constructed based on the head impact frequency and the proportion of severe injuries, utilizing a method that incorporates joint probability.

In the last decades, the locomotion of wheeled and tracked vehicles on soft soils has been widely investigated due to the large interest in planetary, agricultural, and military applications. The development of a tire-soft soil contact model which accurately represents the micro and macro-scale interactions plays a crucial role for the performance assessment in off-road conditions since vehicle traction and handling are strongly influenced by the soil characteristics. In this framework, the analysis of realistic operative conditions turns out to be a challenging research target. In this research work, a semi-empirical model describing the interaction between a tire and homogeneous and fine-grained soils is developed in Matlab/Simulink. The stress distribution and the resulting forces at the contact patch are based on well-known terramechanics theories, such as pressure-sinkage Bekker’s approach and Mohr-Coulomb’s failure criterion.

Compared to passenger cars, commercial vehicles have relatively high fuel and energy consumption, relatively high average annual driving mileage, and a wide range of use. Therefore, energy-saving management of commercial vehicles is crucial. For multi-axle distributed pure electric drive commercial vehicles, a dynamic allocation control strategy for driving torque based on energy consumption optimization is proposed. First, the basic idea of the driving torque distribution control strategy was analyzed and a relevant mathematical model was established. Then, the offline optimization of the distribution coefficients of the driving torque for each axle was carried out through a genetic algorithm, and the entire vehicle driving force distribution strategy using the distribution coefficients as an online lookup table was determined.

Tippers used for transporting blue metal, construction and mining material is designed with different types of load body to suit the material being carried, capacity and its application. These load bodies are constructed with high strength material to withstand forces under various operating conditions. Structural strength verification of load body using FEM is conducted, by modelling forces due to payload as a pressure function on the panels of the load body. The spatial variation of pressure is typically assumed. In discrete element method (DEM) granular payload material such as gravel, wet or dry sand, coal etc., can be modelled by accounting its flow and interaction with structure of load body for prediction of force/pressure distribution. In this paper, coupled FE-DEM is used for determining pressure distribution on loading surfaces of a tipper body structure of a heavy commercial vehicle during loading, unloading and transportation.

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.

In the current scenario, manufacturing of heavier products generates colossal waste, generates more CO2 emission, and negatively affects the environment. Customers not only pay higher product costs but also higher operational costs. This in turn demands the need for more recycling. Advanced high strength materials are a key solution to applications demanding higher strength, stiffness, durability & wear requirement, whereas low density materials like aluminium and magnesium won’t be a sustainable choice. With more and more battery electric & fuel cell vehicles, “light weighting” is a key priority. Austempered Ductile Iron (ADI) has a great advantage of superior mechanical properties compared to conventional ductile iron, aluminium alloys and even some steel forgings. Typically, ADI is used for high wear applications, whereas this paper will demonstrate the potential of using ADI for Structural applications.

Synthesized driving cycles which can reflect the real world driving scenarios are essential for electrification and hybridization of powertrains of heavy duty logistics vehicles (HDLV). Current synthetic methods always neglected weight variation which is crucial for logistic vehicle driving scenarios. This paper proposed a method based on multi-dimensional Markov chains and big data to generate typical driving cycles with consideration of vehicle weight and slope. The validation of the synthesized driving cycle was based on a statistical analysis and the adequacy of the representative to real world driving data was demonstrated.

An optically accessible hydrogen-fueled, heavy-duty engine was used to investigate the impact of mixture formation on the early flame kernel propagation and the resulting combustion cyclic variability. Direct injection from a centrally mounted medium-pressure outward-opening hollow-cone injector created a fuel- air mixture with a global equivalence ratio of 0.33. The engine was operated at 1200 RPM with dry air at an intake pressure and temperature of 1.0 bar and 305 K, respectively. The charge was ignited at three different locations using focused-laser ignition to allow for undisturbed flame evolution, and the fuel injection timing and injection pressure were varied to influence the mixture inhomogeneity.

Leaf springs are used for vehicle suspension to support the load. These springs are made of flat sections of spring steel in single or in stack of multiple layers, held together in bracketed assembly. The key characteristics of leaf spring are defined as ability to distribute stresses along its length and transmit a load over the width of the chassis structures. The most common leaf spring steels are carbon steels alloyed with Cr and micro-alloyed with Ti, V and Nb. The specific thermomechanical process and alloying elements result in specific strength and fatigue properties for spring steels. The unique properties which facilitate use of spring steel in leaf spring suspensions are ability to withstand considerable twisting or bending forces without any distortion. The microstructure of these steel determines the performance and reflects the process of steel manufacturing. The performance is mainly determined by evaluating fatigue life durability.

Fuel tank is considered as safety component in the vehicle, and it has to be tested to meet the safety requirements as per AIS 095. Earlier, fuel tanks were manufactured by using Hot dipped cold rolled steel material and the weld zones are applied with Anti-corrosive coating. Few fuel tanks were reported with Corrosion problems. The root cause analysis was carried out considering the raw material, manufacturing process, transpiration, storage and usage. As an improvement, the new fuel tank is designed to eliminate the limitations of the existing fuel tank. 3D modeling was done to check space and mounting requirement in the layout and used for volume calculations. FE analysis was performed to check structural stability. Emphasis given on Interchange-ability to cater the new fuel tanks in place of old as spares requirement. The fuel tank has developed with Alumina steel material.

The thermal and mechanical loads of the engine rise dramatically with the increase in engine power density, which places higher demands on the design of the piston. In this paper, the design development of a steel piston for a marine diesel engine belonging to 190 series heavy-duty diesel engines was studied. The design methods including material selection and structural design were used to finished the preliminary design. In the meanwhile, the design philosophies of the aluminum alloy piston and composite piston for the 190 series diesel engines were used for reference in the design process. The designed steel piston was tested in the engine durability bench test and simulated for reliability. The results showed that the failure of the steel piston occurred at the same position in both the test and the simulation. The cause of cracking in the steel piston was analyzed, and the insufficient strength of the local structure led to high-cycle fatigue failure.

There is an urgent need to decarbonize various industry sectors, including transportation; however, this is difficult to achieve when relying solely on today’s lithium-ion (Li-ion) battery technology. A lack of sufficient supply of critical materials—including lithium, nickel, and cobalt—is a major driving force behind research, development, and commercialization of new battery chemistries that can support this energy transition. Many emerging chemistries do not face the same supply, safety, and often durability challenges associated with Li-ion technology, yet these solutions are still very immature and require significant development effort to be commercialized. Emerging Automotive Battery Chemistries: Hedging Market identifies and evaluates various chemistries suitable for deployment in the automotive industry and describes advantages, disadvantages, and development challenges for each identified technology.

Considering the change of vehicle future power demand in the process of energy distribution can improve the fuel saving effect of hybrid system. However, current studies are mostly based on historical information to predict the future power demand, where it is difficult to guarantee the accuracy of prediction. To tackle this problem, this paper combines hybrid energy management with predictive cruise control, proposing a hierarchical control strategy of predictive energy management (PEM) that includes two layers of algorithms for speed planning and energy distribution. In the interest of decreasing the energy consumed by power components and ensuring transportation timeliness, the upper-level introduces a predictive cruise control algorithm while considering vehicle weight and road slope, planning the future vehicle speed during long-distance driving.

Mixture formation in a hydrogen-fueled heavy-duty engine with direct injection and a nearly-quiescent top-hat combustion chamber was investigated using laser-induced fluorescence imaging, with 1,4-difluorobenzene serving as a fluorescent tracer seeded into hydrogen. The engine was motored at 1200 rpm, 1.0 bar intake pressure, and 335 K intake temperature. An outward opening medium-pressure hollow-cone injector was operated at two different injection pressures and five different injection timings from early injection during the intake stroke to late injection towards the end of compression stroke. Fuel fumigation upstream of the intake provided a well-mixed reference case for image calibration. This paper presents the evolution of in-cylinder equivalence ratio distribution evaluated during the injection event itself for the cylinder-axis plane and during the compression stroke at different positions of the light sheet within the swirl plane.