Commercial Vehicles Research Articles

Improvement of bionic surface of thrust rod ball joint and finite element analysis

The thrust rod is an important component of heavy-duty vehicles. It can transmit force and torque during vehicle driving and play the role of flexible connection. This paper mainly applies the bionic friction-increasing principle of locust foot pads to the rubber surface of the thrust rod ball joint of commercial vehicles. A bionic ball crown-shaped flexible protrusion is constructed on the surface of the rubber ball joint to increase the stiffness of the ball joint. The height, radius and spacing of the bionic flexible protrusion are changed, and the finite element analysis is performed using Abaqus software to study the radial stiffness, deflection stiffness and torsional stiffness of the thrust rod ball joint. The results show that the best effect is achieved when the protrusion height is 1 mm, the radius is 4 mm and the spacing is 10 mm. Finally, the optimal solution is comprehensively analyzed, and the feasibility of the solution is verified through simulation and experiment.

Bionic Optimization Design and Fatigue Life Prediction of a Honeycomb-Structured Wheel Hub.

The wheel hub is an important component of the wheel, and a good hub design can significantly improve vehicle handling, stability, and braking performance, ensuring safe driving. This article optimized the hub structure through morphological aspects, where reducing the hub weight contributed to enhanced fuel efficiency and overall vehicle performance. By referencing honeycombed structures, a bionic hub design is numerically simulated using finite element analysis and response surface optimization. The results showed that under the optimization of the response surface analytical model, the maximum stress of the optimized bionic hub was 109.34 MPa, compared to 119.77 MPa for the standard hub, representing an 8.7% reduction in maximum stress. The standard hub weighs 34.02 kg, while the optimized hub weight was reduced to 29.89 kg, a decrease of 12.13%. A fatigue analysis on the optimized hub indicated that at a stress of 109.34 MPa, the minimum load cycles were 4.217 × 105 at the connection point with the half-shaft, meeting the fatigue life requirements for commercial vehicle hubs outlined in the national standard GB/T 5334-2021.

Electronic brake system-based hierarchical motion control of commercial vehicle for autonomous obstacle avoidance

As a high-level autonomous driving technology, efficient and safe automatic obstacle avoidance on highway is one of the critical and ongoing topics that requires in-depth research for commercial vehicles. Electronic control air pressure brake system, owing to its fast response and active braking ability, is an effective active-chassis technology to function path tracking and stability control in such condition. Yaw motion stability control problem of autonomous driving commercial vehicle based on active braking control with electronic air brake system for automatic obstacle avoidance is investigated. First, a hierarchical yaw motion dynamics control architecture is introduced after vehicle and brake system modeling. The quintic polynomial curve-based trajectory planning method and a Model Predictive Control based trajectory tracking control strategy are formulated. Second, to evade the possible stability losing issue in this circumstance, Cubature Kalman Filter (CKF) is utilized to estimate the vehicle motion states, and a fuzzy PID control-based differential brake stability control strategy is designed for the electronic brake system composed of front-and-rear two sets of dual-channel pressure regulator and ABS solenoid valve. Finally, the proposed hierarchical yaw stability control strategy for a commercial vehicle in typical obstacle avoidance conditions is comparatively verified based on the joint simulation tools. After the yaw stability control, the peak value of the lateral displacement error of trajectory tracking can be reduced by 44.7%. The yaw stability control strategy based on fuzzy PID control can reduce the yaw rate by 46%–57% and the sideslip angle by 60%–73% under different conditions. The results show that the proposed control strategy can effectively improve the yaw stability of the vehicle while avoiding obstacles at high speed.

The use of sound phonons in the development of NVH treatments for light commercial electric vehicles

Light Commercial Electric vehicles (LCEV) are becoming increasingly popular due to their environmental benefits and lower operating costs, making them a sustainable choice for businesses looking to reduce their carbon footprint and save fuel expenses. However, unlike Saloon and SUV electric vehicles LCEV's have to be potentially configured for a wide variety of operating roles including parcel delivery, mini-buses, retail wagons, ambulances and mobile workshops to name just a few. Consequently, when considering their refinement aspects during their development it has become economically restrictive to base this on actual physical prototypes. Acoustic modelling provides a suitable alternative, but any software package must be highly flexible so that multiple configurations can be examined without requiring time consuming re-modelling. This paper describes the use of sound phonons in an interactive GUI for the successful development process of an LCEV from target setting through to final optimised NVH package creation. The project involved full vehicle model creation via donor CAD, of a current ICE LCV, which was morphed into an EV to include an under-floor battery and rear drive system. Sub-system models of areas such as the interior bulkhead, battery pack insulation and EV encapsulation were also integrated during the optimisation process.

Annoyance caused by simultaneous exposure to noise and seat vibrations inside of a mini excavator: multimodal interaction and the effects of changes in low-frequency content of the sound signal

Drivers of commercial vehicles are exposed to noise and vibrations during their occupation. The signal characteristics of these exposures can lead to different degrees of annoyance perception, even below the legal daily exposure limits. In addition, simultaneous exposure to sound and vibration may lead to potential interaction effects between the two stimuli, influencing the total annoyance perception. Therefore, a perception experiment was designed to ask the participants about the perceived total annoyance caused by simultaneous noise and seat vibrations in commercial vehicles, presenting modified sound and seat vibrations, recorded inside of a mini-excavator. Multimodal interaction effects of noise and vibrations were investigated by changing the intensity of both stimuli. Furthermore, the influence of low-frequency signal components of the sound signal with and without simultaneous seat vibrations was investigated by specific changes in the sound spectrum.

Torque and heat transfer characteristics in Taylor–Couette turbulence with an axially grooved cylinder

To describe the aerodynamic and thermal effects in the flow between the slotted stator and rotor of electric motors, we have conducted direct and large eddy simulations using the lattice Boltzmann method. The flow between the stator and rotor is influenced by turbulence and Taylor–Couette (TC) vortices. Axial grooves (slots) are incorporated either on the stationary outer cylinder or the rotating inner cylinder. These groove shapes and numbers are designed based on the groove geometry of drive motors used in commercial electric vehicles. The radius ratio of the TC flow configuration in this study is 0.955, and the simulated bulk Reynolds numbers reach up to 21000 which corresponds to the Taylor number of Ta=4.63×108. The characteristics of torque and heat transfer are analysed by comparing cases with and without grooves. Regardless of the groove placement, it is suggested that while the grooved surface effects are not significant on torque and heat transfer performance at Taylor numbers Ta≤107, where Taylor vortices are still evident, the effects become pronounced at Ta≥108 as the flow transitions to the ultimate regime.

Pass-by noise regulation - Uncertainties reduction thanks to tire sound emission modelling

The UN regulation R51-03 on vehicle sound emissions enters its third phase in July 2024, with the challenging level of 68 dB(A) to achieve for most of passenger cars and light commercial vehicles. The Lurban indicator, as calculated in the regulation, is a weighted average of acceleration and constant rolling speed tests. Thus, the tire sound emissions represent by far the first contributor to the vehicle compliance. Therefore, it is crucial to understand how tire sound changes under the effects of speed, acceleration, or temperature. In this paper, a study on tire sound behavior is presented. It is based on repeated measurements of pass-by sound emissions of a set of tires, under various conditions of speed, acceleration, and ambient temperature. Among a huge variety of tire sound emission models, a regression algorithm is used to identify the model that fits the best to the measured tire sound emissions data. This tire sound emission model is then used to foresee the impacts of Regulation R51-03 updates, aiming at reducing the uncertainties induced by temperature and test track discrepancies, by correcting the tire sound contribution. The effects of this correction on the uncertainties can be anticipated by the model.

Comparison of Several Energy-Efficient Control Laws Using Energetic Macroscopic Representation for Electric Vehicles

Energy transition and decarbonization present significant challenges to transportation. Electric machines, such as motors and generators, are increasingly replacing internal combustion engines to reduce greenhouse gas emissions. This study focuses on enhancing the energy efficiency of electric machines used in vehicles, which are predominantly powered by batteries with limited energy capacity. By investigating various control strategies, the aim is to minimize energy losses and improve overall vehicle performance. This research examines two types of electric motors: Permanent Magnet Synchronous Motor (PMSM) and Induction Motor (IM). Real-time loss measurements were conducted during simulated driving cycles, including acceleration, constant speed, and braking phases, to mimic typical driving behavior. The simulation utilized characteristics from commercial vehicles, specifically the Renault Zoé and Bombardier eCommander, to assess the controls under different configurations. This study employed the Energetic Macroscopic Representation (EMR) formalism to standardize the analysis across different motors and controls. The results demonstrate significant loss reductions. The controls investigated in this study effectively reduce energy losses in electric motors, supporting their applicability in the automotive industry.

India's Shift to Electric Mobility

The Automotive sector is a pivotal contributor to India’s economic growth and contributes 49% to India’s manufacturing GDP. In FY24, the country produced approximately 49 lakh passenger vehicles, 9.9 lakh three-wheelers, 214.7 lakh two-wheelers, and 10.7 lakh commercial vehicles. The world’s primary modes of transportation are facing two major problems: rising oil costs and increasing carbon emissions. As a result, electric vehicles (EVs) are gaining popularity as they are independent of oil and do not produce greenhouse gases. However, despite their benefits, several operational issues still need to be addressed for EV adoption to become widespread. This research delves into the evolution of EVs over time and highlights their benefits, including reducing carbon emissions and air pollution. India's transition from traditional internal combustion engines (ICE) to electric vehicles (EVs) is driven by a combination of environmental, economic, and policy factors. This shift is aimed at reducing the country's dependency on fossil fuels, lowering carbon emissions, and promoting cleaner air, particularly in urban areas plagued by pollution. Government initiatives such as the Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME) scheme.

Artificial intelligence abnormal driving behavior detection for mitigating traffic accidents

Annually, a tragic toll of 1.3 million lives is lost on roads across the globe, with tens of millions more suffering injuries or disabilities. The necessity for precise detection of abnormal driving behavior is paramount in reducing traffic accidents. This paper aims to bridge the gap between normal and abnormal driving patterns, offering near-flawless detection capabilities. This paper presents a novel AI tachograph prototype, the first of its kind, that can classify driving behavior into normal and abnormal in real time with an impressive accuracy of 99.99 %. This high level of accuracy is achieved by using a bias-reduction method. The bias-reduction method focuses on minimizing biases in the dataset, such as surrounding situations, location, driver information, and car types. This approach significantly enhances the prediction accuracy of existing machine learning algorithms. The dataset used for this research is quite extensive, consisting of anomaly data collected from 10,181 commercial vehicles and 12,530 drivers in just 0.1 s. This rich dataset is crucial for building a reliable model. The effectiveness of the proposed method was validated using 10-fold cross validation on 480 k to 540 k instances with 36 determinants. The results clearly demonstrated that reducing bias leads to higher prediction accuracy. The paper also plans to compare the prediction accuracy of balanced and imbalanced datasets. The findings from this research have broader implications as the proposed method can be applied generally to machine learning to improve prediction accuracy.

Influence of meshing stiffness variation on the vibration characteristics of main reduction gears

Abstract The meshing stiffness of the main and passive gears of the main reducer of the rear axle of a commercial vehicle is taken as the object of this study, aiming to optimize the influence of the meshing stiffness of the main and passive gears on the vibration and noise, enhance the meshing performance of the gear teeth, reduce the vibration and noise of the main reducer, and improve the vibration performance of the main reducer. Through UG 3D modeling software and ADAMS dynamics simulation, the dynamics characteristics of hypoid gears under different gear tooth meshing stiffness coefficients are analyzed and simulated. It is concluded that under the meshing stiffness coefficients of 0.8 to 0.9 times, the translational vibration acceleration and angular acceleration of the passive gears are smaller, the translational vibration and torsional vibration are smoother, and it can improve the performance of the meshing vibration of the gear system of the main gear reducer.

Designing of Ecological Model Predictive Control Algorithm for Electric Trucks Platoons with Optimal Energy Consumption

Abstract In response to the problem of motor vehicle exhaust emissions pollution, the development of new energy in China’s truck industry will be an inevitable trend. At present, the penetration rate and market share of pure electric trucks are constantly increasing. The research on electric truck platoons has strong practical significance. This article focuses on the ecological control strategy of pure electric truck platoons. Firstly, a platoon model of four electric trucks is established in Trucksim. The leading vehicle designs an ecological optimal speed dynamic programming algorithm, and in terms of following vehicle tracking control, the battery SOC state motor speed is considered to be improved, Designed an ecological model predictive control algorithm for electric truck platoon with optimal energy consumption. Using real road slope data in the mining area, a Trucksim/Matlab/Simulink joint simulation was conducted. The simulation results showed that compared with traditional constant speed cruise control, the proposed ecological predictive cruise control algorithm for pure electric commercial vehicle platoons saved 9.2577% of the overall battery SOC.

Smart tachographs application in monitoring and controlling the Operation of Vehicles and Drivers in „ITS“ Environment

ITS systems enable information transparency, manageability and improved response of the traffic system, so they have the epithet of intelligent. The application of ITS solutions on tachographs, as devices that record all the activities of truck and bus drivers, is defined in the ISO 14813-1:2015 Standard in the context of remote data transmission from tachographs. In view of the growing problems regarding violations of regulations on working hours and mandatory vacations for mobile workers, frequent manipulations and misuse of tachographs, as well as regarding the state of traffic safety and increasing environmental pollution, the EU has set stricter conditions in the field of driving these commercial vehicles in its regulations, in the manner of implementing the ITS system of smart tachographs, which brings significant benefits, especially in terms of the work of control authorities as entities that influence better compliance with regulations and the enforcement of legal regulations.

Numerical Investigation of the Fuel Tank Sloshing Condition of a Commercial Vehicle

This study investigates the impact of baffles on fuel sloshing behavior within truck fuel tanks using numerical simulations. The volume of the fluid multiphase model is employed to analyze the flow dynamics of 25% diesel fuel in a 250 L tank, modeled in a 3D domain. Two configurations were compared: a tank with baffles and one without. The primary focus is to analyze fuel distribution within the intake port region during vehicle acceleration and deceleration maneuvers. The simulated scenario mimics a realistic driving situation. The vehicle accelerates from 0 km/h to 60 km/h over 10 s, followed by a 3-s braking period to reach a complete stop (0 km/h) at the 13-s mark. The simulation then observes the fuel behavior within the tank for an addi-tional 7 s while the vehicle remains stationary. Results reveal significant differences in fuel behavior between baffled and unbaffled tanks. In the absence of baffles, the sloshing motion is substantial, leading to a complete depletion of fuel in the intake port region for a duration of 3 s during both the acceleration and deceleration phases (between 10 and 13 s). Compared to a standard tank, the presence of baffles significantly reduced the sloshing amplitude by approximately 70%. Furthermore, baffles led to a 50% decrease in pressure variations on the tank walls. Temporary fuel starvation can negatively impact engine performance and combustion efficiency. Conversely, the presence of baffles within the tank effectively mitigates sloshing and ensures continuous fuel presence at the intake port the entire simulation. This suggests that baffles play a crucial role in maintaining a stable and consistent fuel supply to the engine, even during dynamic vehicle maneuvers.

Drive force allocation control based on pump displacement optimization for hydraulic hybrid motor-assisted system

To achieve rational coordination of the front and rear axle torque of commercial vehicles equipped with hydraulic hybrid motor-assisted systems (HHMAS), and further enhance the vehicle’s fuel efficiency and traction capability. A hydraulic pump displacement control strategy based on energy-efficiency-orientation (EEO) is proposed for driving force distribution. Firstly, the efficiency is analyzed from the perspective of system energy flow. Then, considering the time-varying efficiency characteristics of the hydraulic variable pump and hydraulic motor, the stochastic dynamic optimization problem is modeled as a markov decision process, and a value function estimation method is introduced to approximate the optimal energy efficiency of the entire HHMAS. Finally, the results indicate that the EEO strategy can enhance the fuel economy of vehicles, with a fuel-saving rate of 6.3% compared to the wheel-speed-following-control (WSFC) strategy. In addition, the proposed strategy exhibits superior traction capacity and climbing ability compared to the traditional WSFC strategy.

Quantification of the Vertical Load Applied to the Pavement during Cornering Maneuver of a Battery Electric Commercial Vehicle

Quantification of the Vertical Load Applied to the Pavement during Cornering Maneuver of a Battery Electric Commercial Vehicle

Reducing real driving fuel consumption and emissions with a hydraulic hybrid vehicle

We have successfully prototyped and tested the real-driving performance of a hydraulic hybrid heavy commercial vehicle. Hydraulic hybrid driveline technology was fitted to a Euro IV diesel truck equipped with a diesel particulate diffuser/filter and an exhaust gas recirculation system. An AVL portable emissions measurement system was fitted to the test vehicle to quantify gaseous and particle phase emissions species and an on-board diagnostic scan tool was used to obtain data from the trucks electronic control unit. Fuel consumption savings up to 17 % were accomplished in hydraulic hybrid mode when testing on a short urban driving route featuring a high intensity of stop-start activity. Average reductions in solid particle number concentration of 40 % were achieved along with increases in NOx, Hydrocarbons (THCs) and CO. Future work could target improved control system integration of the various driveline components to further reduce fuel consumption and emissions in an improved prototype design.

Self-tuning neural network generalized predictive control and energy consumption optimization for electro-hydraulic composite steering system of commercial vehicle

Self-tuning neural network generalized predictive control and energy consumption optimization for electro-hydraulic composite steering system of commercial vehicle

An adaptive multi-objective optimization method for structure-connection-performance design of commercial vehicle cab

A variable screening-approximate model-adaptive multi-optimization algorithm integrated method is proposed to solve the high-dimensional nonlinear problems for lightweight optimization of cabs. Firstly, a full-parametric body-in-white model of the cab is established using implicit parameterization technology, and the simulation analysis of the bending and torsional stiffness, natural modal characteristics, and passive safety are established. Then, considering the structure and connection process parameters, the design variables are screened based on a gray relational analysis-TOPSIS (GRA-TOPSIS). Finally, integrated multi-objective optimization of cab structure-connection-performance is carried out by an adaptive RBF neural network optimization method, and the optimal solution is determined by the GRA-TOPSIS method. Compared with the initial model, the mass of cab is reduced by 3.28% after optimization design. It provides guidance for the lightweight design of body.

Cardiovascular Disease Among Commercial Motor Vehicle Drivers: A Focus on Truck Drivers.

Cardiovascular Disease Among Commercial Motor Vehicle Drivers: A Focus on Truck Drivers.