Browse Topic: Vehicle acceleration

Items (2,412)
The presence of time-varying loads on shell structures can result in the generation of undesirable noise in the time domain. This paper presents a time-domain noise control method based on piezoelectric smart shell structures. Firstly, a coupled time-domain finite element/boundary element method (TDFEM/BEM) is used to calculate the sound pressure radiated from shell structures subjected to arbitrary time-varying loads. Then a classical time-domain CGVF algorithm is used to control the vibration and to suppress the sound radiation from structures. Finally, numerical examples demonstrate a 44.2% reduction in the displacement response, a 35.8% decrease in acceleration response, a 36.2% decline in sound pressure of the central node, and a 28.5% decrease in average surface sound pressure. The results show that after CGVF control, the vibration and radiation noise of the plate/shell structure under time domain load are effectively reduced, which is of great significance in engineering
Zheng, HaoWang, HongfuLi, JingjingZhou, QiangSun, YongZhou, LingZhang, HongliangWang, BaichuanHuang, JunsongLiu, XiaorangYin, Guochuan
Tracked Military Vehicles are well known in armed forces, due to their use and importance in conventional combat, playing a crucial role since World War I until current combats. Also, as it happens in different generations, the environment involved in these wars changes and those vehicles are being used not only in open field situations, but inside residential neighborhoods also. However, despite their relevance, analyses and studies aimed at understanding these vehicles are scarce at the undergraduate level, which creates a gap among the recent graduate engineers that want to learn and understand how tracked vehicles perform in different scenarios. This is important because understanding initial concepts helps to bring more ideas and start more detailed studies in the area. Therefore, to bridge this gap, a detailed dynamic analysis of a tracked military vehicle is conducted using MATLAB with a dynamic model to evaluate performance, level transitions, and acceleration. Additionally
Dalcin, Pedro Henrique KleimRibeiro, Levy PereiraLopes, Elias Dias RossiRodrigues, Gustavo Simão
Safety improvements in vehicle crashworthiness remain a primary concern for automotive manufacturers due to the increasing complexity of traffic and the rising number of vehicles on roads globally. Enhancing structural integrity and energy absorption capabilities during collisions is paramount for passenger protection. In this context, longitudinal rails play a critical role in vehicle crashworthiness, particularly in mitigating the effects of rear collisions. This study evaluates the structural performance of a rear longitudinal rail extender, characterized by a U-shaped, asymmetric cross-section, subjected to rear-impact scenarios. Seventy-two finite-element models were systematically developed from a baseline configuration, exploring variations in material yield conditions, sheet thickness, and targeted geometric modifications, including deformation initiators at three distinct positions or maintaining the original geometry. Each model was simulated according to ECE R32 regulation
Souza Coelho Freitas, Victor dePereira, Romulo FrancoSouza, Daniel Souto de
In order to reduce conflicts between vehicles at intersections and improve safety, an optimization model of traffic sequence allocation is studied and established for the heterogeneous traffic scenario of connected autonomous vehicles and manual vehicles. With the minimum safe traffic time as constraint, the right of way is allocated to vehicles according to the microscopic traffic characteristics of heterogeneous traffic flow fleet movement and the phase of signal lights, and the optimal trajectory planning control of each vehicle and evaluation indicators are established. A jointly simulation running environment is built using VISSIM and MATLAB. The simulation results indicate that at the micro level, collaborative control slows down the waiting time for manually driven vehicles and improves the utilization of green light travel time. At the macro level, as the penetration rate of connected autonomous vehicles increases, the sum of squares of vehicle acceleration gradually decreases
Yuan, ShoutongLi, ZhiqiangLiu, TianyuYu, Zhengyang
Although the number of trucks is low, their accident rate is high, and the consequences of accidents are severe. This paper is based on GPS data from 100 trucks, with each trip chain defined by a vehicle’s stay time greater than 20 minutes. The kinematic parameters for each trip chain are then extracted, and the entropy weight method is used to calculate the weights of various parameters. A random forest model is applied to select 11 key indicators, including speed and acceleration. The entropy weight-TOPSIS algorithm is used to assess the risk of each trip chain for the trucks. Different combinations of continuous and discontinuous trip chain scenarios are constructed. Finally, support vector machines (SVM) and decision tree methods are used for risk prediction under different trip chain combinations. The results show that the 11 selected key indicators provide an accuracy of 95.74% for describing the sample. In general, the SVM model shows better prediction accuracy than the decision
Huang, YunheXiong, ZhihuaLi, Jiayu
Automatic driving technology can achieve precise control of the vehicle. Compared with manual driving, it can greatly avoid bad driving behaviors such as rapid acceleration, rapid deceleration, and idle driving, more stable, efficient and safer control of vehicles, thus reducing energy consumption and pollution emissions, has great potential for eco-driving. Previous research on eco-driving car-following strategy is usually based on the current vehicle state. However, the real driving scene is extremely complex and changeable, which makes the existing research easy to fall into the dilemma of local optimal solution when dealing with complex long-term planning tasks, and it is difficult to gain comprehensive insight into the path of global optimal solution. According to the literature, bad driving behaviors such as rapid acceleration and rapid deceleration have a great impact on the energy consumption and emissions of vehicles, in order to realize eco-driving, planning control method
Luo, ShijeZhao, Qi
With the development of intelligent networking technology and autonomous driving technology, how to efficiently and safely schedule intelligent networked autonomous vehicles at signalless intersections has become a research hotspot in traffic management. Based on this, this article first designs an objective function that considers both intersection traffic efficiency and intersection traffic safety, taking into account constraints such as safe distance, speed, acceleration, etc., and constructs a signal free intersection CAV traffic scheduling model. On this basis, a model solving algorithm based on rolling ant colony algorithm is proposed. Simulation experiments show that compared with typical signal control methods, this method can significantly improve intersection traffic efficiency and reduce the number of conflicts.
Zhao, YingjieLiu, XiaomingMa, ZechaoWang, Yuanrong
Large-spacing truck platooning offers a balance between operational safety and fuel savings. To enhance its performance in windy environments, this study designs a control system integrating both longitudinal and lateral motions. The longitudinal control module regulates the inter-vehicle spacing within a desired range while generating a fuel-optimal torque profile by minimizing unnecessary decelerations and accelerations. The lateral control module ensures lateral stability and maintains alignment between the trucks to achieve the expected fuel savings. A two-truck platoon is simulated with a 3-sec time gap under varying wind conditions, using experimental data from the on-road cooperative truck platooning trials conducted in Canada. The control system effectively remains spacing errors within the preset safety buffer and limits lateral offsets to 0.07 m, ensuring safe and stable platooning in windy environments. Additionally, the smoother speed profiles and reduced lateral offsets
Jiang, LuoShahbakhti, Mahdi
This article entails the design, manufacturing, application, testing, and analysis/discussion of a controller area network (CAN)–based vehicle safety system that detects vehicle failure such as brake failure, gear failure, tire blowouts, and other failures that can be monitored using digital or analogue sensors. The aim and objectives are to implement a real-life tire blowout on an Iveco S-Way Euro III and design a system that sends out CAN-based messages using J1939 protocol to the Iveco S-Way Euro III to downshift the gears, retarders, activate the limp mode braking system, activate the hooter, and activate the hazards. The system is split into five sections: (1) detection and activation, (2) gear control system, (3) retarder control system, (4) braking control system, and (5) hooter and hazard control system; while analyzing the: acceleration in the lateral, longitudinal, and vertical acceleration (g) vs. time (s), vehicle speed (km/h), rate of deflation (s), and the steering torque
Rampath, AmaanStopforth, RiaanProctor-Parker, Craig
Semi-trailer trains are the main force of highway freight. In a complex environment with multiple vehicles, accidents are easily caused by complex structures and driver operation problems. Intelligent technology is urgently needed to improve safety. In view of the shortcomings of existing research on its dedicated models and algorithms, this paper studies the intelligent decision-making and trajectory planning of semi-trailer trains under multiple vehicles. A local trajectory planning method based on global path planning and Frenet coordinate decoupling based on the improved A* algorithm is proposed. The smooth weight transition function and B-spline curve are introduced to optimize the global path. The polynomial function is combined with the acceleration rate to optimize the local trajectory. TruckSim, Prescan and Simulink are used to build a joint simulation platform for multi-condition verification. The simulation results show that the search efficiency of the improved A* algorithm
Song, ZeyuanGeng, Shuai
This study delves into the dynamics of three-wheeled Personal Mobility Vehicles (PMVs) equipped with an active tilting mechanism. In three-wheeled vehicles with a single front wheel, the risk of tipping over during sudden braking and sharp turning is often highlighted. To address this issue, the authors have focused their research on three-wheeled PMVs with two front wheels and one rear wheel, equipped with an active tilting mechanism. Previous studies using dynamic simulation tools have demonstrated that such PMVs possess higher obstacle avoidance capabilities compared to motorcycles and even passenger cars. However, these simulations were based on the assumption of avoidance maneuvers without braking, and no studies have yet examined the behavior of three-wheeled PMVs with an active tilting mechanism under the more complex conditions of braking during turning. Therefore, prior to conducting dynamic simulations under braking and turning conditions, this study aims to clarify the
Haraguchi, TetsunoriKaneko, Tetsuya
In general-purpose small SI engines, it is necessary to reduce fuel consumption under operating conditions involving repeated starts and stops. In other words, the energy distribution during the transition from 0 rpm to idling speed is a crucial factor. At startup, the SI engine must be driven by a motor, and the electrical energy required should be minimized. However, the engine must accelerate during this process, and the required electrical energy is influenced by factors such as compression, friction, and moments of inertia. The purpose of this research is to experimentally clarify the conditions for minimum energy starting in SI engines. Specifically, the effect of the moment of inertia was eliminated by using a motor to maintain a constant engine speed, thereby enabling the isolation and measurement of electrical energy consumed by friction. The electrical energy required to overcome the moment of inertia can be determined by comparing it with the energy consumed when
Matsuura, YusukeTanaka, Junya
A road simulator reproduction method was developed to reproduce the off-road conditions of utility vehicles in a laboratory setting. Off-road running behavior can be reproduced by considering the effects of inertial forces from jump landings owing to uneven terrain and slow-speed navigation. However, extremely low-frequency components and behaviors, including inertial forces from jumps, vehicle acceleration and deceleration, are difficult to reproduce with a normal road simulator in the limited test space of a laboratory. Therefore, it is common practice to intentionally remove input components below 1 Hz. Alternatively, inertial forces can be reproduced by adding a restraining device to the sprung mass of the vehicle along the wheel-axle inputs. Therefore, the former method excludes extremely low-frequency components, whereas the effects between actuators, which increase the test complexity and time required, should be canceled in the latter method. Furthermore, the restraining device
Miyasaka, TakahiroShimizu, Ryota
This study proposes a novel control strategy for a semi-active truck suspension system using an integral–derivative-tilted (ID-T) controller, developed as a modification of the TID controller. The ant colony optimization (ACO) algorithm is employed to tune the controller parameters. Performance is evaluated on an eight-degrees-of-freedom semi-active suspension system equipped with MR dampers. The objective is to minimize essential dynamic responses (displacement, velocity, and acceleration) of the sprung mass, cabin, and seat. The controller also considers the nonlinear effects including suspension travel, pitch dynamics, dynamic tire loads, and seat-level vibration dose value (VDV). System performance is assessed under both single bump and random road excitations. The ACO-tuned ID-T controller is compared against passive suspension, MR passive (OFF/ON), and ACO-tuned PID and TID controllers. Simulation results demonstrate that the proposed controller achieves superior performance in
Gad, S.Metered, H.Bassiuny, A. M.
To solve the problems of trajectory prediction and obstacle avoidance of self-vehicles in autonomous driving, a obstacle avoidance algorithm that combines trajectory prediction and vehicle motion planning is proposed. Firstly, in this paper, Unscented Kalman filter and constant acceleration model, namely UKF + CA, as well as Hidden Markov model, namely HMM, are combined together. Predict the trajectory of the vehicle in front and integrate the prediction results obtained by these two methods, which can improve the accuracy of the prediction. Then, in the Frenet coordinate system, this paper adopts the methods of dynamic programming and quadratic programming to generate the planning trajectory of the self-aircraft. After that, this paper conducts collision detection between the fusion trajectory of the preceding vehicle and the planning trajectory of the self-vehicle. If there is a risk of collision, a virtual obstacle will be generated and the path will be re-planned to avoid the
Cao, ZhengShen, Yong-FengHu, Hao-DongOuyang, Le-Wen
Michigan Technological University (MTU) responded to and was awarded Broad Agency Announcement (BAA) Number: W56JSR-18-S-0001 through the Army Rapid Capabilities and Critical Technologies Office (RCCTO). The delivered performance enhanced HMMWV offers increased mobility with over 50% increase in acceleration, improving maneuverability and significant operational range with extended mission duration. Additionally, with on-board energy storage, the vehicle provides extended silent watch and silent mobility capabilities enabling low acoustic and thermal signatures, along with on-board and export vehicle power enabling the powering of mission systems. This paper details the characteristics and performance of an HMMWV with a hybridized powertrain that was designed to meet and demonstrate these benefits.
Worm, ZanderKiefer, DylanSchmidt, HenryPutrus, JohnathonRizzo, DeniseSubert, DaveDice, PaulNaber, Jeffrey D.
The growing demand for improved air quality and reduced impact on human health along with progress in vehicle electrification has led to an increased focus on accurate Emission Factors (EFs) for non-exhaust emission sources, like tyres. Tyre wear arises through mechanical and thermal processes owing to the interaction with the road surface, generating Tyre Road Wear Particles (TRWP) composed of rubber polymers, fillers, and road particles. This research aims to establish precise TRWP airborne EFs for real-world conditions, emphasizing in an efficient collection system to generate accurate PM10 and PM2.5 EFs from passenger car tyres. Particle generation replicates typical driving on asphalt road for a wide selection of tyres (different manufacturers, price ranges, fuel economy rating). Factors such as tyre load, speed and vehicle acceleration are also considered to cover various driving characteristics. The collection phase focuses on separating tyre wear particles from potential
Kontses, DimitriosDimaratos, AthanasiosKaimakamis, ThomasVizvizis, GeorgeOuzounis, RafailKoutsokeras, OdysseasSamaras, Zissis
This article presents a novel mechanical model for simulating the behavior of pavement deflection measuring systems (PDMS). The accuracy of the model was validated by comparing the acceleration of the new model with the data achieved through experimental tests fusing a deflection measurement system mounted on a Ford F-150 truck. The experimental test for the PDMS is carried out on a random road profile, generated by an inertial profiler, over a 7.4-mile (12 km) loop around a lake near Austin, Texas. Integrating a reliability-based optimization (RBO) algorithm in a PDMS aims to optimize system parameters and reduce vibrations effectively. The PDMS noises and uncertainties make it crucial to use a robust system to ensure the stability of the system. This article presents a robust algorithm for considering the uncertainties of PDMS parameters, including the damping coefficients and spring stiffness of the supporting brackets. Moreover, it considers the variation of system parameters, such
Yarmohammadisatri, SadeghSandu, CorinaClaudel, Christian
The diversity of excitation sources and operating modes in hybrid electric vehicles (HEVs) exacerbates the torsional vibration issues, presenting significant challenges to the vehicle’s overall noise, vibration, and harshness performance. To address the complex torsional vibration challenges of the HEVs, this study proposed an active–passive collaborative vibration suppression approach. In terms of passive suppression, a multi-condition parameter optimization scheme for the torsional vibration dampers is designed. In terms of active suppression, a fuzzy control–based electronically controlled damper is proposed, and a hybrid feedforward–feedback motor torque compensation strategy is developed. Simulation results demonstrated that the proposed method reduces the root mean square value of the angular acceleration by over 65% under acceleration and idle conditions and the maximum transient vibration value by 55% during the engine starting condition.
Yan, ZhengfengLiu, ShaofeiHuang, TianyuZhong, BiqingBai, XianxuHuang, Yin
This research primarily addresses the issue of resistance model setting for chassis dynamometers or EIL (engine-hardware-in-the-loop) systems under various loads. Based on the data available from the heavy-duty commercial vehicle coast-down test reports, this article proposes three methods for estimating coasting resistance. For heavy-duty commercial vehicles that have not undergone the coast-down test, this article proposes the GA-GRNN (AC) model to predict coasting resistance. Compared to the GA-BPNN model proposed by previous studies, the new model, which achieves 93% prediction accuracy, demonstrates higher estimation accuracy. For heavy-duty commercial vehicles that have undergone the coast-down test, the coasting equal power method proposed in this article can estimate the coasting resistance under various loads. The accuracy and stability of the new method are verified by several coast-down tests. Compared to the existing method proposed by existing scholars, the new method has
Liang, XingyuSun, ShangfengLi, TengtengZhao, Jianfu
Human driver errors, such as distracted driving, inattention, and aggressive driving, are the leading causes of road accidents. Understanding the underlying factors that contribute to these behaviors is critical for improving road safety. Previous studies have shown that physiological states, like raised heart rates due to stress and anxiety, can influence driving behavior, leading to erratic driving and an increased risk of accidents. In this study, we conducted on-road tests using a measurement system based on the Driver-Driven vehicle-Driving environment (3D) method. We collected physiological signals, specially electrocardiography (ECG) data, from human drivers to examine the relationship between physiological states and driving behaviors. The aim was to determine whether ECG can serve as an indicator of potential risky driving behaviors, such as sudden acceleration and frequent steering adjustments. This information enables automated driving (AD) systems to intervene in dangerous
Ji, DejieFlormann, MaximilianBollmann, JulianHenze, RomanDeserno, Thomas M.
The lack of recorded acceleration and limited Delta-V (ΔV) resolution in many vehicle event data recorders necessitates the development of a method to predict continuous vehicle acceleration based on ΔV responses. This study developed a method of obtaining continuous acceleration by regressing pulse functions (triangular, half-sine, haversine) and polynomial functions (orders 3–6) to a ΔV curve and deriving the corresponding acceleration–time curve. The effectiveness of this method was demonstrated using real-world ΔV response data from front and rear-end collisions. Comparisons were performed between peak and average acceleration values from each front and rear-end crash pulse. Results indicated that a triangular pulse function predicted similar peak acceleration values to the vehicle’s actual acceleration in frontal and rear-end impacts. Average acceleration in frontal impacts was best predicted utilizing a fifth-order polynomial, while a sixth-order polynomial demonstrated the best
Westrom, ClydeAdanty, KevinShimada, Sean D.
Vehicular accident reconstruction is intended to explain the stages of a collision. This also includes the description of the driving trajectories of vehicles. Stored driving data is now often available for accident reconstruction, increasingly including gyroscopic sensor readings. Driving dynamics parameters such as lateral acceleration in various driving situations are already well studied, but angular rates such as those around the yaw axis are little described in the literature. This study attempts to reduce this gap somewhat by evaluating high-frequency measurement data from real, daily driving operations in the field. 813 driving maneuvers, captured by accident data recorders, were analyzed in detail and statistically evaluated. These devices also make it possible to record events without an accident. The key findings show the average yaw rates as a function of driving speed as well as the ratio between mean and associated peak yaw rate. Beyond that, considerably lower yaw rates
Fuerbeth, Uwe
To define a test procedure that will provide repeatable measurements of a vehicle’s maximum acceleration performance for launch and passing maneuvers and standardize time zero used in reported results.
Light Duty Vehicle Performance and Economy Measure Committee
The frequency and amplitude content of powertrain noise is motor torque and speed dependent and tends to influence the driver’s subjective perception of the vehicle. This provides manufacturers with an opportunity to drive product differentiation through consideration of powertrain noise in early stages of the development cycles for electric vehicles (EVs). This paper focuses on the evaluation of customer preference and perception of acoustic feedback from different powertrain design options based on targeted powertrain orders and expected wind and road masking during high acceleration maneuvers. A jury study is used to explore customer feedback to a two-stage gearbox design with AC permanent magnet motor order combinations. The subjective influence of order spacing, dominant frequency content and the number of audible orders is studied to understand aural perspective product differentiation opportunities.
Joodi, BenjaminJayakumar, VigneshConklin, ChrisPilz, FernandoIyengar, ShashankWeilnau, KelbyHodgkins, Jeffrey
Centralization of electrically driven hydraulic power packs into the body of aircraft has increased attention on the noise and vibration characteristics of the system. A hydraulic power pack consists of a pump coupled to an electrical motor, accumulator, reservoir, and associated filter manifolds. In previous studies, the characteristics of radiated acoustic noise and fluid borne noise were studied. In this paper, we focus on the structure-borne forces generated by the hydraulic pump characterized through blocked force measurements. The blocked force of the pump was determined experimentally using an indirect measurement method. The indirect method required operation with part under test fixed to an instrumented receiver structure. Measured operational accelerations on the receiver plate were used in conjunction with transfer function measurements to predict the blocked forces. Blocked forces were validated by comparing directly measured accelerations to predicted accelerations at
Smither, MatthewTuyls, ZacharyPatel, PratikYan, XinHerrin, David
The active sound synthesis system of electric vehicles plays an important role in improving the sound perception and transmission of working condition information inside the vehicle. Nowadays, the active sound synthesis system inside the vehicle has become standard equipment in electric vehicles of major electric vehicle manufacturers to meet the user groups' demand for driving and riding experience. In order to enrich the driving experience of electric vehicles and automatic transmission vehicles, the sound performance should be close to the immersiveness and dynamic feedback brought by traditional manual transmission fuel vehicles. Based on the active sound synthesis algorithm in the car, this paper proposes an adaptive shift sound quality control strategy suitable for complex and changeable working conditions, with the aim of simulating the real shift sound of the engine. First, the motor speed offset is accurately calculated based on the transmission ratio of each gear of the
Zhou, XilongLiu, ZhienXie, LipingYu, ShangboLu, ChihuaGao, XiangYongsheng, Wang
The acceleration vibe of a car's engine can be enhanced and a brand-specific auditory identity can be created via active sound design. Currently, experienced engineers are desperately required when the active sound design for car acceleration roar was processing, which consumed substantial time and human resources. Therefore, it is critical to conduct a research on the evaluation model for estimating car acceleration sound quality to improve sound design efficiency and reducing costs. 1,003 acceleration roars samples of common cars were collected in this paper, all of which could be commonly heard by the road. Nine psychoacoustic objective parameters, such as loudness, sharpness, and roughness, were calculated through Artemis Suite software, establishing a database for the sound quality of car acceleration sounds.Moreover, subjective evaluations of sound playback and objective data analysis were conducted to obtain the ratings of acceleration sounds. Firstly, five objective
Xiong, ChenggangXie, LipingZhang, ZheweiShi, WeijieQian, YushuLiu, Zhien
Contemporary Japanese society relies heavily on vehicles for transportation and leisure. This has led to environmental concerns owing to vehicle emissions, prompting a shift toward environmentally friendly alternatives, such as clean diesel and electric vehicles. Clean diesel vehicles aim to reduce harmful emissions, whereas electric vehicles are favored because of their minimal emissions and quiet operation. However, the lack of engine noise in electric vehicles can make it difficult for drivers to perceive speed changes, potentially increasing the risk of accidents, and simply amplifying all sounds is not viable because it may cause discomfort. Therefore, this study explored how deviations from expected engine sounds affect the perceived sound quality and vehicle performance assessment. Unlike traditional gasoline-powered and clean diesel vehicles, electric vehicles produce very little running noise, which makes road surface noise more prominent. Given the novelty of electric
Nitta, MisakiIshimitsu, ShunsukeFujikawa, SatoshiIwata, KiyoakiNiimi, MayukoKikuchi, MasakazuMatsumoto, Mitsunori
This study examines the acoustic properties of engine-knocking sounds in gasoline engines, arising from misfires during spark ignition that negatively affect driving performance. The aim was to understand the frequency characteristics of acceleration sounds and their connection to the proximity of the order components. The study also explores “booming,” where two different frequencies of sounds occur simultaneously, potentially linked to the unpleasant nature of engine knocking. Using a sinusoidal model, we generated engine acceleration sound models with 5th-, 10th-, and 15th-order components, including engine knocking. Two types of sound stimuli were created: one with the original amplitude (OA) and one with a constant amplitude (CA) for each component order, emphasizing the order-component proximity in CA sounds. Aural experiments with 10 participants in an anechoic room using headphones and the MUSHRA method revealed an inverse relationship between OA and CA ratings as the component
Suzuki, RyuheiIshimitsu, ShunsukeNitta, MisakiSakakibara, MikaHakozaki, TomoyukiFujikawa, SatoshiIwata, KiyoakiMatsumoto, MitsunoriKikuchi, Masakazu
In this study, vibration characteristics inside an electric power unit at gravity center where direct measurement is impossible were estimated by using virtual point transformation to consider guideline for effective countermeasures to the structure or generated force characteristics inside the power source. Vibration acceleration, transfer function and the generated force in operation at the gravity center of the electrical power source were obtained by vibration characteristics at around the power source which can be measured directly. In addition, the transfer functions from the gravity center to the power source attachment points on the product were also estimated. And then, the contribution from the gravity center to the power unit attachment point was obtained by multiplying generated force with the transfer function. As results, the obtained total contribution was almost same with the actual measured vibration at the attachment point. Furthermore, the rotational contribution
Kubo, RyomaHara, KentaYoshida, Junji
Hurricane evacuations generate high traffic demand with increased crash risk. To mitigate such risk, transportation agencies can adopt high-resolution vehicle data to predict real-time crash risks. Previous crash risk prediction models mainly used limited infrastructure sensor data without covering many road segments. In this article, we present methods to determine potential crash risks during hurricane evacuation from an emerging alternative data source known as connected vehicle data that contain vehicle speed and acceleration information collected at a high frequency (mean = 14.32, standard deviation = 6.82 s). The dataset was extracted from a database of connected vehicle data for the evacuation period of Hurricane Ida on Interstate-10 in Louisiana. Five machine learning models were trained considering weather features and different traffic characteristics extracted from the connected vehicle data. The results indicate that the Gaussian process boosting and extreme gradient
Syed, Zaheen E MuktadiHasan, Samiul
Testing was conducted in daytime and nighttime conditions to evaluate the performance of the Automatic Emergency Braking and Forward Collision Warning systems present on both a 2020 and 2022 Kia Telluride. The 2022 Kia Telluride was tested during the day at speeds between 35 and 70 miles per hour, while the 2020 Kia Telluride was tested both during the day and at night at speeds between 35 and 60 miles per hour (mph). The daytime testing of both the 2020 and 2022 Kia Telluride utilized a foam stationary vehicle target. The nighttime testing of the 2020 Kia Telluride utilized a live 2006 Chevrolet Tahoe as the target with the brake lights on. Testing measured the Time to Collision (TTC) values of the visual/audible component of the Forward Collision Warning (FCW) that was presented to the driver. Further, testing also quantified the timing and magnitude of the two-phase response of the Automatic Emergency Braking (AEB) system. The results of both sets of testing add higher speed FCW and
Harrington, ShawnPatrick-Moline, PeytonNagarajan, Sundar Raman
Testing was conducted to evaluate the performance of the 2020 Jeep Grand Cherokee’s Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) collision mitigation systems at speeds between 35 and 70 miles per hour (mph). Two different 2020 Jeep Grand Cherokee’s were utilized under varying testing conditions in order to evaluate the performance of their collision mitigation systems. A total of 40 tests were conducted: 29 tests were conducted during daytime and 11 tests were conducted at nighttime. Testing measured the Time to Collision (TTC) values of the visual/audible component of the Forward Collision Warning that was presented to the driver. In addition, the testing quantified the TTC response of the Automatic Emergency Braking (AEB) system including the timing and magnitude of the automatic braking response. The results of the testing add higher speed FCW and AEB testing scenarios to the database of publicly available tests for the 2020 Jeep Grand Cherokee.
Harrington, ShawnLieber, VictoriaNagarajan, Sundar Raman
The paper provides a detailed analysis of the transmission system design under the single motor drive scheme, with a focus on the 2024 Formula SAE (FSAE). The selection of the motor type is determined based on race rules and battery box output power limits. In terms of transmission ratio design, this study takes into account the car's power, balancing acceleration ability and maximum speed to determine an optimal transmission ratio through theoretical calculations and empirical values. Furthermore, it explores how to optimize overall drive system performance by considering technical parameters, power requirements, economic considerations of each system assembly, and validates these findings through software simulations. Notably, significant improvements in reliability are achieved with the newly designed transmission system and wheel rim system while also proposing lightweighting methods for key components. We have carried out extensive verification in both simulation and real vehicle
Wang, LiuxinLi, ChengfengZhu, XiranLiu, Minmin
Accurate reconstruction of vehicle collisions is essential for understanding incident dynamics and informing safety improvements. Traditionally, vehicle speed from dashcam footage has been approximated by estimating the time duration and distance traveled as the vehicle passes between reference objects. This method limits the resolution of the speed profile to an average speed over given intervals and reduces the ability to determine moments of acceleration or deceleration. A more detailed speed profile can be calculated by solving for the vehicle’s position in each video frame; however, this method is time-consuming and can introduce spatial and temporal error and is often constrained by the availability of external trackable features in the surrounding environment. Motion tracking software, widely used in the visual effects industry to track camera positions, has been adopted by some collision reconstructionists for determining vehicle speed from video. This study examines the
Perera, NishanGriffiths, HarrisonPrentice, Greg
To address the issue of high accident rates in road traffic due to dangerous driving behaviors, this paper proposes a recognition algorithm for dangerous driving behaviors based on Long Short-Term Memory (LSTM) networks. Compared with traditional methods, this algorithm innovatively integrates high-frequency trajectory data, historical accident data, weather data, and features of the road network to accurately extract key temporal features that influence driving behavior. By modeling the behavioral data of high-accident-prone road sections, a comprehensive risk factor is consistent with historical accident-related driving conditions, and assess risks of current driving state. The study indicates that the model, in the conditions of movement track, weather, road network and conditions with other features, can accurately predict the consistent driving states in current and historical with accidents, to achieve an accuracy rate of 85% and F1 score of 0.82. It means the model can
Huang, YinuoZhang, MiaomiaoXue, MingJin, Xin
Hydro-pneumatic suspension is widely used due to its favorable nonlinear stiffness and damping characteristics. However, with the presence of parameter uncertainties and high nonlinearities in the hydro-pneumatic suspension system, the effectiveness of the controller is often suboptimal in practical applications. To mitigate the influence of these issues on the control performance, an adaptive sliding mode control method with an expanded state observer (ESO) is proposed. Firstly, a nonlinear mathematical model of hydro-pneumatic suspension, considering seal friction, is established based on the hydraulic principle and the knowledge of fluid mechanics. Secondly, the ESO is designed to estimate the total disturbance caused by the nonlinearities and uncertainties, and it is incorporated into the sliding mode control law, allowing the control law to adapt to the operating state of the suspension system in real time, which solves the effect of uncertainties and nonlinearities on the system
Niu, ChangshengLiu, XiaoangJia, XingGong, BoXu, Bo
In this paper, the equivalent elliptic gauge pendulum model of liquid sloshing in tank is established, the pendulum dynamic equation of tank in non-inertial frame of reference is derived, and the dynamics model of tank transporter is constructed by force analysis of the whole vehicle. A liquid tank car model was built in TruckSim to study its dynamic response characteristics. Aiming at the problem that the coupling effect between liquid sloshiness in tank and tank car can easily affect the rolling stability of vehicle, the roll dynamics model of tank heavy vehicle is established based on the parameterized equivalent elliptic gauge single pendulum model, and the influence of different lateral acceleration and suspension system on the roll stability is studied. The results show that the coupling effect between the motion state of the tank car and the liquid slosh lengthens the oscillation period of the liquid slosh in the tank, and the amplitude of the load transfer rate of the tank car
Yukang, Guo
Drivers sometimes operate the accelerator pedal instead of the brake pedal due to driver error, which can potentially result in serious accidents. To address this, the Acceleration Control for Pedal Error (ACPE) system has been developed. This system detects such errors and controls vehicle acceleration to prevent these incidents. The United Nations is already considering regulations for this technology. This ACPE system is designed to operate at low speeds, from vehicle standstill to creep driving. However, if the system can detect errors based on the driver's operation of the accelerator pedal at various driving speeds, the system will be even more effective in terms of safety. The activation threshold of ACPE is designed to detect operational errors, and it is necessary to prevent the system from being activated during operational operations other than operational errors, i.e., false activation. This study focuses on the pedal operation characteristics of pedal stroke speed and
Natsume, HayatoShen, ShuncongHirose, Toshiya
This study is to demonstrate a vehicle dynamics simulation process to assess vehicle vibration performance. A vehicle dynamics model including non-linear tuning elements and flexible vehicle body is simulated on ride roads. The goal of the simulation is acceleration responses at the passenger locations in frequency domain. Body interface loads are recovered from the vehicle dynamic simulations. Frequency response function (FRF) of the body structure is ready in a fashion that input forces are applied to all body interface locations to the suspension and powertrains. This will give acceleration response sensitivity of the body structure to each body interface. The sum of body interface loads multiplied by FRF at each interface produces acceleration responses in frequency domain. A mid-size sedan model was used to demonstrate the process. A full vehicle dynamics model using Ansys Motion was simulated on a virtual ride road at a constant speed. The body loads were recovered in time domain
Hong, Hyung-JooMaddula, Pavan KumarJun, Hyochan
Two wheelers motorcycles are used for many purposes e.g. commuting from one place to another, long highway rides, racing and off-roading. Motorcycles which are used in off-road conditions require higher suspension strokes to absorb large oscillations due to terrain conditions. These motorcycles undergo jumps of varying heights and different vehicle orientations. In some of the dynamic situations front wheel may land on the ground before the rear and in other cases it may be vice versa. To make sure that the vehicle is durable enough to withstand loads in such operating conditions, vehicle drop test was developed in test lab where vehicle is dropped from predefined heights in both front & rear wheel landing conditions. Same test case is simulated in multibody dynamics to capture loads at important connections of the frame. This paper presents the correlation exercise carried out to validate MBD model and simulation process with test data captured during lab test. Accelerations at
Jain, Arvind KumarNirala, Deepak
One challenge for autonomous vehicle (AV) control is the variation in road roughness which can lead to deviations from the intended course or loss of road contact while steering. The aim of this work is to develop a real-time road roughness estimation system using a Bayesian-based calibration routine that takes in axle accelerations from the vehicle and predicts the current road roughness of the terrain. The Bayesian-based calibration method has the advantage of providing posterior distributions and thus giving a quantifiable estimate of the confidence in the prediction that can be used to adjust the control algorithm based on desired risk posture. Within the calibration routine, a Gaussian process model is first used as a surrogate for a simulated half-vehicle model which takes vehicle velocity and road surface roughness (GD) to output the axle acceleration. Then the calibration step takes in the observed axle acceleration and vehicle velocity and calibrates the Gaussian process model
Lewis, EdwinaParameshwaran, AdityaRedmond, LauraWang, Yue
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