Vehicle Parts Research Articles

Parameter Optimization and Mechanical Properties of Laser Cladding of 316L Stainless Steel Powder on G20Mn5QT Steel

G20Mn5QT steel has excellent mechanical properties and is widely used in key components of rail vehicles. However, during the operation of high-speed vehicles, wear and tear will inevitably occur. In this paper, laser cladding technology was selected to successfully prepare 316L stainless steel coating. The optimum processing parameters were obtained with a laser power of 2300 W, a scanning speed of 500 mm/min, and a powder feeding speed of 14 g/min. The microstructure of 316L coating is mainly composed of planar crystals, cellular crystals, columnar crystals, and equiaxed crystals. Through range analysis, it is found that the microhardness, wear resistance, and micro-shear strength of the cladding layers increase with the increase of laser power, while the tensile strength and yield strength increase first and then decrease with the increase of laser power. Under the optimized process parameters, the low-temperature impact toughness, elongation, tensile strength, and yield strength of the cladding layer were 97.6%, 24%, 10.9%, and 32.5% higher than that of the G20Mn5QT substrate, respectively. An excellent combination of strength and toughness was achieved by cladding 316L alloy on the surface of the G20Mn5QT substrate, which can meet the requirements of remanufacturing fractional key vehicle parts.

LiDAR-Based Sensor Fusion SLAM and Localization for Autonomous Driving Vehicles in Complex Scenarios

LiDAR-based simultaneous localization and mapping (SLAM) and online localization methods are widely used in autonomous driving, and are key parts of intelligent vehicles. However, current SLAM algorithms have limitations in map drift and localization algorithms based on a single sensor have poor adaptability to complex scenarios. A SLAM and online localization method based on multi-sensor fusion is proposed and integrated into a general framework in this paper. In the mapping process, constraints consisting of normal distributions transform (NDT) registration, loop closure detection and real time kinematic (RTK) global navigation satellite system (GNSS) position for the front-end and the pose graph optimization algorithm for the back-end, which are applied to achieve an optimized map without drift. In the localization process, the error state Kalman filter (ESKF) fuses LiDAR-based localization position and vehicle states to realize more robust and precise localization. The open-source KITTI dataset and field tests are used to test the proposed method. The method effectiveness shown in the test results achieves 5-10 cm mapping accuracy and 20-30 cm localization accuracy, and it realizes online autonomous driving in complex scenarios.

Environment-oriented disassembly planning for end-of-life vehicle batteries based on an improved northern goshawk optimisation algorithm.

Due to environmental pollution and resource shortages, the electric vehicle industry has been developing swiftly, and the market demand for batteries, as an essential part of electric vehicles, has also surged. Proper disassembly of end-of-life vehicle batteries (ELV batteries) is necessary to achieve the integrity and closure of their life cycle, promote the development of green remanufacturing, effectively reduce the pollution of the environment caused by metal ion leakage, and reduce people's dependence on natural resources to a certain extent. To schedule the disassembly operations of ELV batteries more rationally and further promote their disassembly quality and efficiency, this paper proposes a dual-objective disassembly sequence planning (DSP) optimisation model, which aims to minimise the hazard index and energy cost during ELV battery disassembly operations. Since the proposed model is a complex NP-hard optimisation problem, this study develops an efficient metaheuristic algorithm for solving this model based on the northern goshawk optimisation algorithm. The main algorithm adds two types of discrete recombination operators and a local search operator. At the same time, the predatory behaviour of the goshawk is optimised by combining the characteristics of the disassembly sequence planning problem to improve its performance. Finally, the disassembly of the battery of a Tesla Model 1 is used as a case study to demonstrate the effectiveness and feasibility of the proposed method.

A Novel Design Method of an Evolutionary Mold Cooling Channel Using Biomimetic Engineering.

In this study, an evolutionary cooling channel, a new methodology for designing a conformal cooling channel, was proposed. This methodology was devised by imitating the way that a plant's roots grow towards a nutrient-rich location. Additionally, Murray's law was applied to increase the cooling efficiency through minimizing the pressure loss of the cooling water inside the cooling channel. The proposed method was applied to the specimen shape to verify the concept, and it was confirmed that efficient cooling was achieved by applying it to the headlamp lens cover part of an actual vehicle. When this methodology was applied, the temperature deviation of the part could be improved by about 46% in just third generations, and the pressure loss could be reduced by about 10 times or more compared to the result of applying the straight-line cooling channel.

Effect of Bumper Thickness with Collision Simulation of Passenger Vehicles

The finite element method is the most common method used to solve engineering and mathematical model problems. Related solution areas include structural analysis, heat transfer, mass transport and electromagnetic potential. FEM is a specific numerical method used to solve partial differential equations in two or three space variables. To solve a problem, FEM breaks up a large system into smaller, simpler parts called finite elements. First, a three-dimensional model of the system to be analyzed is produced. While defining the model, the materials and connection types found in the model are also deter-mined. Afterwards, the model is divided into small parts and analyzed under specified conditions. A crash test will be conducted in this study. For this, the conditions of the vehicle parts will be examined by hitting a wall under the conditions of which the model design of the vehicle is determined. Crash tests were carried out for two different bumper thicknesses on the same vehicle and the test results were examined. The vehicle speed is modeled as 20 m/s in the simulation carried out from the moment of impact until 0.14 seconds later. The effect of buffer thickness on axial displacements at impact and energy changes are presented.

Evolution of Equipment in Electromobility and Autonomous Driving Regarding Safety Issues

Over the years, an increase in the traffic of electric and hybrid electric vehicles and vehicles with hydrogen cells is being observed, while at the same time, self-driving cars are appearing as a modern trend in transportation. As the years pass, their equipment will evolve. So, considering the progress in vehicle equipment over the years, additional technological innovations and applications should be proposed in the near future. Having that in mind, an analytical review of the progress of equipment in electromobility and autonomous driving is performed in this paper. The outcomes of this review comprise hints for additional complementary technological innovations, applications, and operating constraints along with proposals for materials, suggestions and tips for the future. The aforementioned hints and tips aim to help in securing proper operation of each vehicle part and charging equipment in the future, and make driving safer in the future. Finally, this review paper concludes with a discussion and bibliographic references.

Analysis Of Enterprise Resources Planning (ERP) Implementation Planning In Car Parts Distributor Companies (Case Study: CV. Persatuan Putra Mandiri)

CV Persatuan Putra Mandiri is one of the distributors engaged in the sale of vehicle parts, especially cars. This company uses accounting software to manage its daily business activities, but in its implementation, there are still obstacles that can hinder the development of this company itself. The purpose of this research is to provide clear knowledge to the company regarding the weaknesses and strengths that exist in the current system and help companies to determine which ERP system is suitable for the company and its implementation process to the company's business processes. Therefore, this ERP planning stage begins with identifying problems, identifying ongoing business processes and then making system proposals that are described using Business Process Model Notation (BPMN). The next stage is to analyze the ERP system that may be able to accommodate the overall business process. The method that the author uses in this research is descriptive qualitative, where we obtain data from the description of the existing business processes and by conducting interviews with direct sources, namely employees in the company. We did a comparison of several ERP software commonly used in similar companies, and we got the results where the most suitable ERP software for this research is Oracle because it feels best suited to the needs and conditions of the existing business processes in the company.

Analysis of the Maintenance of Operational Facilities for the PKP-PK Unit in Supporting Aviation Safety at Iskandar Pangkalan Bun Airport

Care and maintenance of PKP-PK operational vehicle facilities, one of the things that must be done by personnel to provide accident services in the airport area, is the same as at Iskandar Pangkalan Bun airport for the care and maintenance of main and supporting vehicles in accordance with the Regulations of the Directorate of Civil Aviation KP.14 of 2015. The purpose of this study was to find out qualitatively about the components that must be considered every day in maintaining operational vehicles at Iskandar Pangkalan Bun Airport. The research design is a qualitative study in the form of a case study using observation sheets and in-depth interviews with PKP-PK personnel and PKP-PK units at Iskandar Pangkalan Bun Airport. The results of the study indicate that the obstacles experienced by PKP-PK personnel in carrying out maintenance and maintenance of operational vehicles, namely the procurement of vehicle parts, in which the PKP-PK unit at Iskandar Airport has various car brands (manufacturing factories).

Review on Flow Controls for Vehicles Aerodynamic Drag Reduction

Reducing aerodynamic drag in automobiles has been one of the focuses in automotive industry as it will increase vehicles performance and reduce power consumption which subsequently save the environment. Drag is a force that tend to pull the vehicle backwards. Pressure drag is the major contributor to drag of vehicle which caused by lower pressure in the rear area compared to front of vehicle. When vehicle moves forward, the stagnation point occurs in the front part of vehicle. The airflow then goes over the vehicle and separate at the back due to adverse pressure gradient. Thus, flow separation is created in the rear area of vehicle as indicated by the wake. Wake is a low-pressure region that need to be reduced so that the pressure between the front and rear could be reduced to minimize the drag. Flow control is introduced to delay this flow separation and it has been categorized as active and passive. Active flow controls require power input while passive flow controls do not need power input. This review article will explore those studies on flow controls applied in automobiles and investigate their working mechanisms along with research gaps detected. Relative comparison of effectiveness for each flow control is unfeasible as the parameters used differs but this problem can be resolved. Standard parameters need to be used in future researches in order address the discrepancy of results obtained from numerous studies around the globe. A current flow control technique is proposed to be conducted in UTM Aerolab to further investigate this interesting flow field.

Influence of multiple slips and magnetic effects on the quadratic convective flow over a vertical wedge

AbstractThis paper investigates the quadratic convective flow of Williamson nanoliquid with the impacts of velocity, thermal and concentration slips over a vertical wedge. Further, the magnetic effects and the Buongiorno two‐phase nanoparticle model are considered. The study of this type of flows over a vertical wedge appears in various engineering applications such as thermal insulation, engine parts of vehicles, aerospace, crude oil extraction and heat exchangers. The physical problem is formulated as a set of quadratic coupled partial differential equations (PDEs), which are dimensional. Further, the dimensionless PDEs obtained by the non‐similar transformations are solved with the aid of the implicit finite difference method and the Quasilinearization technique. The effects of slip parameters, streamwise coordinate, fluid material parameters and magnetic field on various gradients and profiles are explored through graphs. The greater values of concentration slip and thermal slip parameters improve the concentration and temperature profiles, but the fluid's velocity is reduced with the velocity slip parameter. The streamwise coordinate significantly influences the fluid's velocity more than the concentration and temperature profiles. The velocity and skin friction coefficient are pronounced more for a higher wedge angle. Also, the numerical results of this investigation compared to similar works that have been published before show that they are very consistent.

Complex Effects of Hemp Fibers and Impact Modifiers in Multiphase Polypropylene Systems

Natural fibers-reinforced polymer composites have progressed rapidly due to their undeniable advantages. Most of the commercial polypropylene (PP)-based materials are characterized by either high impact toughness or high stiffness, while the manufacture of PP composites with both good toughness and stiffness is challenging at present. In this work, poly[styrene-b-(ethylene-co-butylene)-b-styrene] (SEBS) and poly(styrene-b-butadiene-b-styrene) (SBS) copolymers were used in different amounts as modifiers in PP/hemp fibers (HF) composites, with the aim to use them for electrical vehicle parts. The interface in these multiphase systems was controlled by the addition of maleated polypropylene (MAPP). SEBS and SBS showed different effects on the elongation at break of the blends and the corresponding composites due to the HF that stiffened the multiphase systems. Similarly, a different action of MAPP was observed in the composites containing SEBS or SBS: higher Young's and storage moduli were obtained for the composite containing SBS, while greater elongation at break and impact strength values were recorded for the SEBS-containing system. In addition, a remarkable dispersion in the MAPP-containing composite and two times smaller average particle size were revealed by the SEM analysis for the SEBS particles compared to the SBS ones. The higher affinity of SEBS for PP compared to that for SBS and the different morphological characteristics of the systems containing SEBS and SBS may explain the different effects of these impact modifiers on the mechanical properties of the composites. The composites developed in this work were designed as substitutes for the fully synthetic polymeric materials or metal components used in the manufacturing of automotive parts.

Risks of Leukemia in Various Industrial Groups in Korea: A Retrospective National Cohort Study

It is known that occupational exposure to specific agents is associated with leukemia. However, whether the occupational risks of leukemia differ among various industrial groups remains unclear. Therefore, the purpose of this study was to elucidate the occupational risks of leukemia among different worker groups by industry. Data for a total of 11,050,398 people from the National Health Insurance System's claim data from 2007 to 2015 were analyzed. By cohort inclusion of workers whose industry had not changed for three years and with total workers as a control group, the risk for a specific industry group was expressed as an age-standardized incidence ratio (SIR). Among groups by industry, 'Manufacture of motor vehicles and engines for motor vehicles', 'Sale of motor vehicle parts and accessories', and 'Personal care services' showed significantly higher SIRs. In division analysis, the 'Manufacture of other machinery and equipment' and 'Waste collection, treatment and disposal activities' divisions showed significantly higher SIRs than other divisions. We identified an increased risk of leukemia in workers of certain industries in Korea. Based on the results of this study, it is necessary to create a policy to protect workers at risk of leukemia. Various additional studies are needed to protect workers by revealing more precise relationships between individual hazardous substances, processes, and leukemia.

Driving a sustainable road transportation transformation

Driving a sustainable road transportation transformation

Maritime Tracking With Georeferenced Multi-Camera Fusion

Cameras form an essential part of any autonomous surface vehicle’s sensor package, both for COLREGs compliance to detect light signals and for identifying and tracking other vessels. Due to limited fields of view compared to more traditional autonomy sensors such as lidars and radars, an autonomous surface vessel will typically be equipped with multiple cameras which can induce biases when used in tracking if a target is present in multiple image frames. In this work, we propose a novel pipeline for camera-based maritime tracking that combines georeferencing with clustering-based multi-camera fusion for bias-free camera measurements with target range estimates. Using real-world datasets collected using the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">milliAmpere</i> research platform the performance of this pipeline exceeded a lidar benchmark across multiple performance measures, both in pure detection performance and as part of a JIPDA-based tracking system.

Study on the Profit Model of Power Battery Enterprises

In recent years, global ecological environment deterioration, climate warming and other issues have become increasingly prominent. Governments of all countries are promoting the transformation of energy structure and vigorously supporting the new energy automobile industry. As the core part of new energy vehicles, power battery also ushered in a rapid development opportunity. As the most representative enterprise in China’s power battery enterprises, CATL has become the leading enterprise in China’s power battery enterprises by virtue of its first mover advantage, technological advantage and scale advantage in the power battery industry. Taking CATL as an example, this paper analyzes its profit model by using the five elements of profit model, and evaluates its financial performance from three aspects of profitability, cash earning ability and growth ability. It is concluded that the current CATL is a profit model dominated by power batteries, and the lithium battery industry chain is constantly improving its layout. The profit model of the enterprise is not unchanging but changing with the development of the enterprise. CATL has constantly explored and improved the profit model of the enterprise in its business process.

Ungraded tyre performance analysis for Indian road conditions

The safety of tyres is an integral part of an ideal vehicle. Along with the safety, the tyres' emissions are also a concern nowadays. In this article impact of various factors that directly or indirectly impact tyre performance is explored and tested a set of tyres to analyze factors like rolling resistance, minimum breaking energy, endurance, durability, and strength by conducting three tests specified according to the Bureau of Indian Standards and UN Global Technical Regulation. The test outcomes were used to identify the exclusions present in Indian Standards if any, and changes were recommended to align them better with the global standards. As per the tests performed, we reached to the conclusion that we can test the tyres with a higher load threshold, as the value of breaking energy calculated as per IS 15633 was half the value calculated according to UN GTR.

Conformal Frequency Selective Surfaces for Arbitrary Curvature

An algorithm is introduced for generating frequency selective surfaces (FSSs) capable of conforming to any curvature while maintaining the proper size, shape, and spacing of the elements. Compared to traditional projection and mapping methods, the presented algorithm maintains the electromagnetic properties of the FSS array despite the curvature. The algorithm can be used to conform to radomes, parts of autonomous vehicles, or any surface. The algorithm is agnostic to both element design and surface curvature. This allows the user to design a FSS for any curved surface while maintaining its response comparable to a flat array. The algorithm outputs two standard tessellation language (STL) files, one describing the curved surface and the other the elements of the FSS placed onto the curved surface. This makes the algorithm suitable for 3-D printing using systems with more than three axes or for flexible electronics. Several examples of arbitrary surfaces are shown. Lastly, the algorithm was applied to a Jerusalem-cross (JC) FSS on a nonsymmetrical parabolic dome. The dimensions of the parabolic dome were chosen to test the response of the array on a rather extreme surface against a projected array on the same surface. Simulations were carried out using Ansys HFSS from the infinite array to finite arrays to confirm the operation. Three test surfaces were manufactured with measured results found to be in good agreement with the simulation.

Simulation and Experimental Design of Load Adaptive Braking System on Two Wheeler

The braking quality is considered the main execution of the adaptive control framework that impacts the vehicle safety and rides solace astoundingly notably the stopping distance. This research work aims to create a pattern and design of an electromechanically adjusted lever that multiplies the applied braking force depending on the inputs given by the sensors to reduce the stopping distance of the vehicle. It is carried out using two main parts of the two-wheeler vehicle: the first part deals with the detection of load acting on the vehicle and identifying the required braking force to be applied, and the second part deals with the microcontroller which activates the stepper motor for varying the mechanical leverage ratio from various loads on the vehicle using two actively movable wedges. The electromechanically operated variable braking force system is developed to actuate the braking system based on the load on the motorcycle. The MATLAB simulation and experimental work are carried out for various loading (driver and pillion) conditions on a two-wheeler. The results indicate that the proposed electronically operated braking system is more effective than the conventional braking system for various loads and vehicle speeds. Specifically, the stopping distance of the vehicle is decreased significantly by about 4.9% between the conventional braking system and the simulated proposed system. Further, the experimental results show that the stopping distance is condensed by about 4.1%. The validation between simulated and experimental results revealed a great deal with the least error percentage of about 0.8%.

State-of-the-Art Wayside Condition Monitoring Systems for Railway Wheels: A Comprehensive Review

In recent decades, there has been a constant demand for faster, longer, and safer railway networks. This also brings challenges for condition monitoring systems in modern railway vehicles. More specifically, critical parts of railway vehicles like wheels degrade over time due to various operational and environmental reasons. Different dynamic effects such as skidding/sliding over the track and the presence of contamination between wheel-rail cause various wheel defects. Faulty wheels ultimately lead to the derailment of railway vehicles. To avoid worst situations like railway derailments, various research has been conducted for developing efficient condition monitoring systems for railway wheels. In addition, there have been some commercial condition monitoring products that can be deployed with railway vehicles. These systems incorporate various sensors such as strain gauges and vision sensors to collect data for diagnosis and prognosis. Various methods have been explored but yet there is a broad research gap in terms of developing advanced onboard condition monitoring systems. With the progress in technology, advanced systems with Machine Learning/Deep Learning methods can provide more efficient and robust condition monitoring of dynamic railway systems. Considering the need for advancement in condition monitoring systems for railway vehicles, a comprehensive review of existing condition monitoring systems for railway wheels is conducted in this paper. The review is aimed at understanding the feasibility and potential of new methods for modern railways. This paper provides a detailed overview of studies on the existing wayside systems and reports their advantages and disadvantages concerning its recently emerging counterpart on-board monitoring systems. Data acquisition systems and analysis methods are critically reviewed which could assist in developing more efficient and reliable condition monitoring systems for railway wheels. This article also reviews the current progress of wayside systems and their limitations. The article is targeted at the researchers and engineers working in this domain, who can pave the way for developing advanced and cost-effective condition monitoring systems for railway wheels using modern technologies.

A Back Propagation Neural Network-Based Radiometric Correction Method (BPNNRCM) for UAV Multispectral Image

Radiometric correction is one of the most important preprocessing parts of unmanned aerial vehicle (UAV) multispectral remote sensing data analysis and application. In this article, a back propagation (BP) neural network-based radiometric correction method (BPNNRCM) considering optimal parameters was proposed. First, we used different UAV multispectral sensors (K6 equipped on the DJI M600, D-MSPC2000 equipped on the FEIMA D2000) to collect training, validation, testing and cross-validation data. Second, the radiometric correction results of BP neural network with different input variables and hidden layer node number were compared to select the best combination of input parameters and hidden layer node number. Finally, the radiometric correction accuracy and robustness of BP neural network considering the optimal parameters were verified. When the number of nodes in the input layer was five (digital number, UAV sensor height, wavelength, solar altitude angle, and temperature) and the number of nodes in the hidden layer was eight, the BP neural network had the best comprehensive performance in training time of train set and accuracy of validation/test set. In the aspect of accuracy and robustness, the absolute errors of test and cross-validation images' surface reflectance obtained by the BPNNRCM were all less than 0.054. The BPNNRCM had smaller average absolute error (0.0141), mean squared error (0.0003), mean absolute error (0.0141) and mean relative error (7.1%) comparing with empirical line method and radiative transfer model. In general, the research results of this article prove the feasibility and prospect of BPNNRCM for radiometric correction of UAV multispectral images.