bluuebunny/crossref_metadata_2025 huggingface dataset:
The Integrated Trajectory Tracking, Yaw Stability and Roll Stability Model Predictive Control for Autonomous Vehicle in Limited Handling Condition
Authors: Li Boyuan , Li Wenfei , Hua Wei , Velenis Efstathios
Published: April 2023

In the current literature, the research studies on the trajectory tracking control and stability control strategy for autonomous vehicles in limited condition mostly focus on the yaw plane control, but few of the studies have considered the combined control performance of trajectory tracking, yaw and roll stability, and the roll stability is critical under the extreme cornering condition for autonomous vehicles. Aiming at the above shortages, this study designs the model predictive control (MPC) strategy for the autonomous vehicles under the limited handling condition, which integrates the front and rear wheel active steering control, four-wheel independent drive and braking control and active suspension control to comprehensively improve the trajectory tracking accuracy, yaw plane stability and roll plane stability of the vehicle under the extreme condition. In the internal prediction model of the MPC, the yaw plane dynamics, roll plane dynamics and suspension system models are considered to better coordinate the yaw plane and roll plane dynamics control. Also the different control delays of steering, driving, braking and suspension control actuators are considered in the model. In addition, in order to improve the vehicle yaw stability, the soft constraints of wheel longitudinal slip and lateral side-slip angle are designed in the optimization objective function of the MPC. Furthermore, based on the analysis on the coupling effect of the steering, traction or brake and active suspension control on the trajectory tracking and vehicle dynamics stability, the scaling factors of MPC optimization cost function are normalize and carefully tuned to achieve the best performance. Finally, the effectiveness and computational efficiency of the designed integrated MPC strategy is verified by simulation based on high fidelity vehicle dynamics model.
Research on Thermal Recession Compensation Method of Disc Brakes
Authors: Tan Zhi-Fang , Kang Yingzi , Shangguan Wenbin , Wang Weiwei , Jiang Kaihong
Published: April 2023

If a car is braked frequently or at high speed, the thermal decay of brake system performance appears, which reduces the braking performance of the car. To compensate brake moment reduction during braking at thermal decay of brake system, a compensation strategy of brake moment is designed by using “feedforward +PID feedback” to pressure at wheel braking cylinder. The trigger and exit conditions of the strategy for the wheel cylinder pressure are proposed based on the threshold. A vehicle model consisting braking system is established if a vehicle runs at straight line, and the braking distance and braking acceleration are estimated, the results shown that the thermal decay compensation control strategy proposed in this paper can reduce the braking distance and braking time. A braking system experiment if a car runs at straight line is carried out, it demonstrates that if temperature of a disc brake is higher than 300°C, the thermal decay will occur, and friction coefficient decreases by 16.7% compared with the nominal friction coefficient. Brake thermal decay compensation strategy proposed in this paper can enhance braking safety performance if thermal decay happens.
Test Results of Tires for All-Terrain Vehicles from a Flat-Trac® Machine
Authors: Zagorski Scott , Heydinger Gary
Published: April 2023

This paper presents tire data from an All-Terrain Vehicle (ATV). Data is collected on a Flat-Trac® machine where force and moment data were collected for three tires: one front tire and two rear tires. Tests were conducted at slip angles of +/-28 degrees, varying normal loads and inclinations angles. Additionally, tests were conducted at varying levels of inflation pressure. Key parametric data such as aligning moment, cornering and vertical stiffness levels are presented. One key finding from this study is that, in general, as inflation pressure increases cornering and aligning moment stiffness decreases. This effect is counter to typical passenger vehicle tires, where higher inflation pressure usually results in higher stiffness levels. Using results from the tire test data, understeer calculations are made for a vehicle under varying loading conditions.
Advanced Modelling of Frequency Dependent Damper Using Machine Learning Approach for Accurate Prediction of Ride and Handling Performances
Authors: Lenka Visweswara Rao , Anthonysamy Baskar , Thanapati Alok Ranjan , Deshmukh Chandrakant Ramrao
Published: April 2023

Accurate ride and handling prediction is an important requirement in today's automobile industry. To achieve the same, it is imperative to have a good estimation of damper model. Conventional methods used for modelling complex vehicle components (like bushings and dampers) are often inadequate to represent behaviour over wide frequency ranges and/or different amplitudes.

This is difficult in the part of OEMs to model the physics-based model as the damper’s geometry, material and characteristics property is proprietary to part manufacturer. This is also usually difficult to obtain as a typical data acquisition exercise takes lots of time, cost, and effort. This paper aims to address this problem by predicting the damper force accurately at different velocity/ frequency and amplitude of measured data using Artificial Neural Networks (ANN). The predicted damper force histories were found to be quite accurate as the error in ride and handling between the measured and the thus predicted time histories at various locations were found to be less than 15%. This approach is found to be extremely useful in collecting enormous amounts of customer usage data with minimum instrumentation and small sized data loggers. This has given a big fillip to customer usage data collection in the automotive industry, where the size of the loggers has been a constraint in the collection of such data.

New modelling methods circumvent these limitations by using laboratory measurements with neural networks. The new methods enable accurate simulation for nonlinear, frequency dependent components, having multiple inputs and outputs, under arbitrary excitation. This paper describes one such method, known as Empirical Dynamics Modelling. Examples are presented for vehicle shock absorbers. Benefits and limitations are discussed, along with requirements for interfacing to a conventional virtual prototyping environment. Results show particularly good correlation between simulation and testing compare with traditional method.
New Controller Evaluation Techniques for Autonomously Driven Heavy-Duty Convoys
Authors: Snitzer Philip , Stegner Evan , Bentley John , Bevly David M. , Hoffman Mark
Published: April 2023

Platooning vehicles present novel pathways to saving fuel during transportation. With the rise of autonomous solutions, platooning becomes an increasingly apparent sector requiring the application of this new technology. Platooning vehicles travel together intending to reduce aerodynamic resistance during operation. Drafting allows following vehicles to increase fuel economy and save money on refueling, whether that be at the pump or at a charging station. However, autonomous solutions are still in infancy, and controller evaluation is an exciting challenge proposed to researchers. This work brings forth a new application of an emissions quantification metric called vehicle-specific power (VSP). Rather than utilize its emissions investigative benefits, the present work applies VSP to heterogeneous Class 8 Heavy-Duty truck platoons as a means of evaluating the efficacy of Cooperative Adaptive Cruise Control (CACC). VSP creates a bridge between types of passenger vehicles to compare emission rates via estimating powertrain effort to maintain current conditions (speed, acceleration, road grade, etc.). In this study, different controller strategies and platoon configurations are examined to determine the applicability of VSP to controller evaluation. Experiments were completed at the National Center for Asphalt Technology (NCAT) circuitous track, the American Center for Mobility’s (ACM) freeway loop, and a straight section of NCAT’s track dubbed “ideal” for platooning efficiency. One truck is analyzed and compared to a lead truck, where VSP traces are calculated at each time step of experimentation. The influence of road grade, platoon size, and platooning position is considered in this study. Because the calculation of VSP considers an isolated driving environment, it effectively assesses the controller’s ability to reduce energy consumption for platooning vehicles.
Trajectory Planning on Autonomous Truck with Dual-Modular Chassis Using Artificial Potential Field and Polynomial
Authors: Liu Tao , Shen Yanhua , Wang Haoshuai , Liu Zuyang
Published: April 2023

Autonomous truck with modular chassis has the characteristics of high driving flexibility and strong load capacity. It can be equipped with different numbers of modular chassis according to the task requirements. The application of autonomous truck can solve the problems of traffic accidents and shortage of drivers effectively, which is the development trend of trucks in the future. For the collision-free trajectory planning problem of dual-modular chassis autonomous truck, this paper designs a hierarchical local trajectory planner that combines the artificial potential field method with polynomial curve fitting method. This planner plans the center of mass trajectory firstly, and then generates the modular chassis trajectories according to the position relationship between the center of mass and the chassis. The center of mass local trajectory cluster satisfying the environment constraints and truck motion constraints is obtained by polynomial curve fitting method for sampling the road discrete points in the parameter space. In order to make the evasive maneuver of dual-modular chassis autonomous truck start earlier to make the obstacle avoidance process safer, a three-dimensional repulsive potential field is constructed based on artificial potential field method around the obstacle. The repulsive potential field of the obstacle is regarded as the constraint of the collision-free trajectory of the truck. The optimal collision-free trajectory is selected by constructing multi-object function. Simulations of obstacle avoidance of dual-modular chassis autonomous truck on different curvature roads with different speeds in Simulink/Simscape environment are conducted to demonstrate performance of the proposed collision-free trajectory planner. The simulation results show that the collision-free trajectory planner based on artificial potential field method and polynomial curve fitting method can make the autonomous truck avoid collision safely and steady on different curvature roads with different speeds.
MPC Based Car-Following Control Considering Uphill and Downhill
Authors: Tu Qingquan
Published: April 2023

At present, most of the longitudinal car-following control algorithms based on model predictive control (MPC) do not consider the influence of the presence of the sloping road on the inter-vehicle distance, resulting in poor tracking capability under ramp conditions. In order to reduce the inter-vehicle distance error under ramp conditions and improve the tracking capability of longitudinal car-following control algorithm. The car-following control algorithm based on MPC considering uphill and downhill is proposed. This algorithm is based on the vehicle structure of fuel passenger cars, and adds a slope angle reconstruction module for implementing slope angle measurement and reducing the complexity of slope angle calculation based on the framework of conventional hierarchical control structure. Meanwhile, in the upper-level controller, the MPC algorithm is improved by categorically discussing the actual inter-vehicle distance on horizontal roads and slope roads, and by introducing offsets that consider the slope of the road into the formula for the desired inter-vehicle distance. In the lower-level controller, the presence of slope resistance and slope angle in the vehicle longitudinal dynamics equation are additionally considered to further improve the accuracy of the lower-level actuators in executing the control signals transmitted from the upper-level controller on the ramp. Finally, the tracking capability of the algorithm is verified by using Carsim & Matlab/Simulink co-simulation platform. The results show that under the control of the car-following control algorithm proposed in this paper, the number of road slope segments is reduced by 60%, and the inter-vehicle distance error is reduced by 15% and 3.1% in the car-following process of uphill and downhill, respectively, compared with the conventional car-following algorithm. The algorithm in this paper has better car-following accuracy on the road with changing slope.
A Comparison Study on Control Strategies for Optimization of an Anti-Lock Brake System Algorithm Based on Tire Force Measurement in Pure and Combined Slip Conditions of an Automobile
Authors: Shaikh Parvez Shagir , Mehta Harshal Piyush , Mallikarjunaiah Umesh , Kamble Vijay , Maurya Mithilesh
Published: April 2023

The Anti-Lock Braking System (ABS) is a safety critical feature primarily used to control slipping of wheels, to maximize available traction and minimize stopping distance. Regulatory authorities of many countries have mandated implementation of an ABS as a compulsory safety feature to be present in all road legal automobiles. Hence, apart from avoiding wheel lock-up, an ABS must also ensure that the vehicle maintains its handling stability and steerability while braking. Thus, it is important that the ABS controller modulate and apply adequate amount of brake cylinder pressure. This paper suggests the use of a Tire Force based algorithm to analyze vehicle behavior and accordingly a control law is employed to modulate the wheel brake pressure. A comparison study has been performed among control methods such as Step Gain Reduced Order Model (SGROM) developed using Machine Learning techniques and Linear Quadratic Regulator (LQR) to determine an optimal control law for brake pressure modulation under pure and combined slip condition.

The SGROM control technique implements a wheel cylinder pressure gain that is a function of vehicle state variables such as input brake pressure, normalized tire force and vehicle speed. The optimum output pressure gain is estimated by using a machine learning technique that is further elaborated in the paper. The LQR control technique regulates wheel cylinder pressure gains by minimizing cost function based on desired braking characteristics.

The control algorithms are evaluated based on standard brake performance tests such as stopping distance, split mu, and brake in turn. Accordingly, an optimal control strategy is selected based on evaluation criteria defined in the standards.
Optimized PID Controller Using Genetic Algorithm for Anti-lock Brake System
Authors: Mohammed Omnia , Metered Hassan , Abdelaziz Taha
Published: April 2023

The anti-lock brake system (ABS) is a vital system in modern vehicles that prevents automotive wheels from locking during an emergency brake. This paper aims to introduce an efficient, optimized proportional integral derivative (PID) controller tuned using a genetic algorithm (GA) to enhance the performance of ABS. The PID control method is a very famous control algorithm employed in numerous engineering applications. The GA is used to solve the nonlinear optimization problem and search for the optimum PID controller gains by identifying the solution to the problem. A mathematical model of ABS is derived and simulated using Matlab and Simulink software. The proposed optimized PID-controlled ABS is compared to the conventional ABS controlled using a Bang-Bang controller. System performance criteria are evaluated and assessed under different road adhesion coefficient values to judge the success of the proposed PID controller tuned using GA. The simulated results indicate that the proposed PID controller can offer a significant improvement of ABS performance under any value of road adhesion coefficient.
Hierarchical Motion Planning and Control Algorithm of Autonomous Racing Vehicles for Overtaking Maneuvers
Authors: Kim Changhee , Yi Kyongsu , Park Jaeyong
Published: April 2023

This paper describes a hierarchical motion planning and control framework for overtaking maneuvers under racing circumstances. Unlike urban or highway autonomous driving conditions, race track driving requires longer prediction and planning horizons in order to respond to upcoming corners at high speed. In addition, the subject vehicle should determine the optimal action among possible driving modes when opponent vehicles are present. In order to meet these requirements and secure real time performance, a hierarchical architecture for decision making, motion planning, and control for an autonomous racing vehicle is proposed. The supervisor determines whether the subject vehicle should stay behind the preceding vehicle or overtake, and its direction when overtaking. Next, a high level trajectory planner generates the desired path and velocity profile in a receding horizon fashion. In order to reduce the computational burden despite maintaining a sufficiently long planning horizon, a low fidelity kinematic vehicle model is utilized for the planner. Finally, a model predictive control (MPC) based low level trajectory tracker generates the lateral and longitudinal control inputs. A high fidelity dynamic vehicle model is introduced to provide a high quality control input for a relatively short control horizon compared with the motion planner. Simulation results demonstrate that the proposed algorithm successfully controls the subject vehicle to deal with preceding opponent vehicles under racing track environments.
Global Off-Road Path Planning of Unmanned Ground Vehicles Based on the Raw Remote Sensing Map
Authors: Zhang Jian , Xie Fei , Wang Chao , Liu Qiuzheng , Hong Ri , Du Jinpeng
Published: April 2023

Unmanned Ground Vehicle (UGV) has a wide range of applications in the military, agriculture, firefighting and other fields. Path planning, as a key aspect of autonomous driving technology, plays an essential role for UGV to accomplish the established driving tasks. At present, there are many global path planning algorithms in grid maps on unstructured roads, while general grid maps do not consider the specific elevation or ground type difference of each grid, and unstructured roads are generally considered as flat and open roads. On the contrary, the unmanned off-road is always a bumpy road with undulating terrain, and meanwhile, the landform is complex and the types of features are diverse. In order to ensure the safety and improve the efficiency of autonomous driving of UGV in off-road environment, this paper proposes a global off-road path planning method for UGV based on the raw image of remote sensing map. Firstly, the raw image is gridded. The map elevation information is assigned based on the digital elevation model (DEM) and the terrain is classified and labeled in the grid map based on the back propagation neural network (BPNN). Based on the reconstructed off-road grid map, a modified A* algorithm considering the safety and efficiency of UGV passage is designed for global path planning on off-road environment. Simulation results based on real off-road environment show that the proposed global planning algorithm can avoid impassable areas and make UGVs drive on high traffic efficiency roads as much as possible.
Road Anomaly Detection and Localization for Connected Vehicle Applications
Authors: Zhu Xiaoliang , Kundu Subrata Kumar
Published: April 2023

Road anomalies pose significant challenges for on-road safety, ride comfort, and fuel economy. The recent advancement of Connected Vehicle technology has made it feasible to overcome this challenge by sharing the detected road hazards information with other vehicles and entities. However, localization accuracies of the detected road hazards are often very low due to noisy detection results and limited GPS sensor performances. In this paper, a cloud based data management system with in-vehicle and on-cloud data processing modules is presented for road hazards detection and localization. Stereo camera and a consumer-grade GPS sensor on a testing vehicle are used to detect road anomaly information, e.g., type, size, and location, where a novel in-vehicle data processing module is implemented based on Kalman Filter and Phase Adjustment. For hazards data shared from all connected vehicles, an on-cloud data processing module is designed to further improve anomaly localization accuracy based on clustering. The whole system was tested in a parking lot with potholes, debris, and road bumps. Experimental results show that the hazards localization accuracy could be significantly improved from 7.4m to 1.4m with 84% accuracy using the proposed system. The proposed real-time system could bring significant benefits for commercial vehicles, and transportation companies with improved safety and ride quality.
Development of a Baja SAE Data Acquisition System
Authors: Hubbard Nicholas , Mynderse James A.
Published: April 2023

A vehicle-level data acquisition (DAQ) system was developed and implemented on the Lawrence Technological University (LTU) Baja SAE vehicle. This low-cost Arduino-based DAQ system is capable of accurately and repeatedly measuring Baja SAE specific vehicle parameters and storing them for offline analysis. While expandable for the needs of future teams, the developed DAQ system includes measurement of vehicle wheel speed, CVT pulley speeds, suspension position, CVT belt temperature, steering load, and steering angle.

The development of the DAQ system architecture and the development of the angular speed and suspension position measurement subsystems are the focus of this work. The processes followed and lessons learned can be used by other Baja SAE and SAE Collegiate Design Series. Each measurement subsystem was designed, fabricated, integrated, and validated on the bench and in-vehicle. Data acquisition software was developed for the DAQ, and offline data processing software was implemented in MATLAB. Finally, the complete system was tested using a combination of industry standard and Baja SAE specific vehicle tests.
A Semantic Segmentation Algorithm for Intelligent Sweeper Vehicle Garbage Recognition Based on Improved U-net
Authors: Liu Yang , Tan Gangfeng
Published: April 2023

Intelligent sweeper vehicle is gradually applied to human life, in which the accuracy of garbage identification and classification can improve cleaning efficiency and save labor cost. Although Deep Learning has made significant progress in computer vision and the application of semantic network segmentation can improve waste identification rate and classification accuracy. Due to the loss of some spatial information during the convolution process, coupled with the lack of specific datasets for garbage identification, the training of the network and the improvement of recognition and classification accuracy are affected. Based on the Unet algorithm, in this paper we adjust the number of input and output channels in the convolutional layer to improve the speed during the feature extraction part. In addition, manually generated datasets are used to greatly improve the robustness of the model. Next, we select the Softmax as the activation function to adjust the classification probability of each category. The cross-entropy function, selected as the loss function, is used to evaluate the fitting ability of the model. We adjust the stride and the size of the feature map in the convolution process to reduce the amount of calculation. The k-fold cross-validation makes full use of the dataset to better optimize the model. Compared with Unet algorithm, the data shows that the improved algorithm can extract more effective features for classification prediction, and simplify the network for parameter selection and optimization, and improve the training speed by 10%. The recognition accuracy is increased by 18% while ensuring the speed, and it has higher MPA and MIoU. This algorithm has good generalization ability to deal with different test sets, which improves the efficiency of the intelligent sweeper vehicle and provides a reference for the design of the semantic segmentation model of garbage classification at the same time.
Numerical Study of the Fuel Efficiency and the Thermal Management of a Fuel Cell Powered Long-Haul Vehicle
Authors: Bauer Martin , Lauer Thomas
Published: April 2023

In the future, conventional powertrains will increasingly be supplied by sustainable energy sources. Long-haul freight transport requires efficient energy storage and the ability to refuel quickly. For this reason, hydrogen-powered PEM fuel cells are being discussed as a future energy source for long-distance vehicles. However, there are numerous challenges in packaging, system cooling and service life. Above all, the dissipation of the fuel cell’s heat losses places high demands on the design of the cooling system due to the relatively low operating temperature.

In the presented study, a complete generic drive train of a long-distance commercial vehicle was set up within a suitable simulation environment to investigate the required sizes of the fuel cell stack, the HV battery, the hydrogen tanks, and the cooling circuit. The thermodynamic and electrochemical data that was necessary to describe the stack, the BoP components, the battery, the coolers, and the drivetrain components were taken from the literature or similar applications.

Afterward, the requested propulsion power, fuel consumption, and cooling demand were analyzed for constant vehicle speed and representative driving cycles. Mountainous highway passages, as typically occurring in the Alpes, were investigated for different ambient temperatures. Detailed loss analyses were carried out for the whole powertrain and visualized in Sankey diagrams.

The results revealed challenging thermal management at high ambient temperatures that may result in degrading fuel cell power when crawling uphill with low vehicle speed. However, the potential and suitability of PEM fuel cells for sustainable long-haul transport could be clearly demonstrated.
Estimates of In-Vehicle Task Element Times for Usability and Distraction Evaluations
Authors: Green Paul , Koca Ekim , Brennan-Carey Collin
Published: April 2023

Engaging in visual-manual tasks such as selecting a radio station, adjusting the interior temperature, or setting an automation function can be distracting to drivers. Additionally, if setting the automation fails, driver takeover can be delayed. Traditionally, assessing the usability of driver interfaces and determining if they are unacceptably distracting (per the NHTSA driver distraction guidelines and SAE J2364) involves human subject testing, which is expensive and time-consuming.

However, most vehicle engineering decisions are based on computational analyses, such as the task time predictions in SAE J2365. Unfortunately, J2365 was developed before touch screens were common in motor vehicles. To update J2365 and other task analyses, estimates were developed for (1) cognitive activities (mental, search, read), (2) low-level 2D elements (Press, Tap, Double Tap, Drag, Zoom, Press and Hold, Rotate, Turn Knob, Type and Keypress, and Flick), (3) complex 2D elements (handwrite, menu use), and (4) for 2D/3D elements (Reach, Swipe, Dwell/Hold, Grab/Grip/Grasp, Release, Draw, Pinch and Spread, and Wave/Shake). A future paper will provide estimates for complex 2D elements and cognitive activities. Most of the time estimates are for young people (ages 18-30) because those data were available. Methods are provided to estimate times for other age groups. These estimates were drawn from recognized data sources including, (1) industrial engineering predetermined time systems (e.g., Methods-Time- Measurement 1 (MTM-1), (2) the Keystroke-Level Model (KLM), (3) the Model Human Processor (MHP), (4) SAE J2365, (5) human-computer interaction studies, and (6) driver-interface studies concerned with estimating and validating task times on touch screens.
Construction of Driver Models for Overtaking Behavior Using LSTM
Authors: Baba Tomohiro , Oikawa Shoko , Hirose Toshiya
Published: April 2023

This study aimed to construct driver models for overtaking behavior using long short-term memory (LSTM). During the overtaking maneuver, an ego vehicle changes lanes to the overtaking lane while paying attention to both the preceding vehicle in the travel lane and the following vehicle in the overtaking lane and returns to the travel lane after overtaking the preceding vehicle in the travel lane. This scenario was segregated into four phases in this study: Car-Following, Lane-Change-1, Overtaking, and Lane-Change-2. In the Car-Following phase, the ego vehicle follows the preceding vehicle in the travel lane. Meanwhile, in the Lane-Change-1 phase, the ego vehicle changes from the travel lane to the overtaking lane. Overtaking is the phase in which the ego vehicle in the overtaking lane overtakes the preceding vehicle in the travel lane. Lane-Change-2 is the phase in which the ego vehicle changes lanes from the overtaking lane to the travel lane after overtaking the preceding vehicle in the travel lane. We analyzed and evaluated the accuracy of the models for the entire experimental scenario and for each model of Lane-Change-1, Overtaking and Lane-Change-2. The constructed models were also evaluated for safety in lane-change situations based on the WP.29 steering equipment regulation of the UNECE, which was defined as Scritical in the Automatically Commanded Steering Function (ACSF) Category C of R79 in WP.29 of UNECE. In the results, the Lane-Change-2 model was identified to be the most accurate of the four phases and the model accuracy was found to be due to epochs and learning rate. All the constructed models satisfied the WP.29 regulation of UNECE. The constructed models which reflected individual characteristics are expected to be applied to ADAS and automated driving technology that conduct overtaking maneuvers.
Optimization of Side Impact Airbag Design Using Response Surface Method
Authors: Shrivastava Abhinav , Behera Dhiren , Reddy Niranjan , Aluru Phani
Published: April 2023

Seat mounted side impact airbags (SIAB) along with side curtain airbags are now a standard passive safety equipment offered by nearly all original equipment manufacturers (OEM) to meet side protection requirements in many regions of the world. While the side curtain airbag is intended to reduce head injury, the SIAB protects the thorax and abdomen region of the driver or passenger in a side crash scenario. An optimized SIAB both in terms of design and deployment threshold has the potential to reduce occupant’s injury level and can prevent fatalities.

Because of the limited space available between the occupant and the side structure of the vehicle, there are significant challenges posed for packaging a SIAB to provide adequate cushioning distance from the intruding parts of the vehicle side structure and spread the impact load over a larger area. Different regulatory requirements in different geographies add further challenges for a common design. Common design is not only cost-effective, but it also simplifies manufacturing.

Exhaustive studies have been published on vehicle structure optimization in a crash scenario, but only a handful of literature is available on SIAB design and development study.

The present work depicts a detailed study of SIAB performance in terms of occupant injury criteria and the effect of various SIAB design parameters under various side crash load cases, such as defined by IIHS, USNCAP, FMVSS and other agencies. Key design parameters effecting the performance are identified and subsequently SIAB design parameters were optimized based on a Response Surface Method (RSM). This study details a process to commonize the SIAB design across the geographies. SIAB parameters are optimized in the current study for load cases in the United States and China. The optimized airbag shape is validated further using Ls Dyna runs. A response-surface-based injury prediction is reasonably consistent with the results of the Dyna.

This approach will allow us to determine the shape of a side pelvic thorax airbag and help to understand how altering different design parameters affects performance (rib injury values).
Optimum design of a Tractor hydraulics system by innovative material development and Correlation with physical testing
Authors: Gunalan Magendran , Gopalan Vijaysankar , Gomes Maxson , Dumpa Mahendra , Perumal Solairaj
Published: April 2023

The tractor usage is growing in the world due to derivative of rural economy and farming process. It needed wide range of implements based on the applications of the customer. The tractor plays a major role in Agricultural and Construction applications. In a tractor, hydraulic system is act as a heart of the vehicle which controls the draft and position of the implement. Hydraulic system consists of Powertrain assembly, 3-point linkage and DC sensing assembly. The design of hydraulic powertrain assembly is challenging because the loads acting on the system varies based on the type of implement, type of crop, stage of farming and soil conditions etc., Hydraulic powertrain assembly is designed based on standards like IS 12207-2019 which regulates the test methods for the system based on the lift capacity of the tractor. In this paper, virtual simulation has been established to optimize the design and perform the test correlation. Now a days finite element analysis is more powerful to predict the durability of the components. Based on the Real-World Usage Pattern (RWUP), Lab and Track conditions. Multi Body Dynamic (MBD) analysis was performed to predicts the loads acting on the hydraulic system. Structural analysis was performed to predict the durability of the components. Based on the initial level of analysis, light weight tractors are performing better in multiple applications. Ferrous casting is one of the major materials are being used in tractor industries for many decades for housings and load bearing members. So based on the initial study, design optimization is done to reduce the mass considering the current manufacturing process and design requirements. Innovative material developed for a hydraulic powertrain component to meet the various load cases considered. Multiple trails were conducted to achieve the consistent mechanical and metallurgical properties considering the current casting practices and infrastructure available in India. Part with new material undergone all the validation cycles and there was no failure observed during physical testing. Correlation study was done to validate this process and achieved 93.8% & 94.7% of strain correlation. Further to correlate the hot spot locations, overload Testing was conducted till failure and failure trend matched with CAE analysis
Quantifying the Sensitive Parameters of the New Energy Vehicles in China
Authors: Saafi Mohamed Ali , Ou Shiqi (Shawn) , He Xin
Published: April 2023

To achieve carbon neutrality by 2060, the Chinese government has put effort into decarbonizing the transportation sector. Consequently, China elaborated a new energy vehicle strategy promoting the production of electric vehicles and expanding into hydrogen (H2) vehicle technologies including fuel cell electric vehicles and H2 internal combustion engine vehicles. The Transportation Energy Analysis Model (TEAM) projects the market penetration as well as energy demand and greenhouse gas emissions in China up to 2050. By integrating the Monte Carlo simulation, this study tests the robustness of TEAM and investigates the key parameters that will shape passenger vehicle sales and emissions in the future. The results show that fuel cell cost, H2 price, and battery cost are the most sensitive parameters for H2 vehicle technologies.
Pre-Design and Feasibility Analysis of a Magneto-Rheological Braking System for Electric Vehicles
Authors: de Carvalho Pinheiro Henrique , Imberti Giovanni , Carello Massimiliana
Published: April 2023

Magneto-Rheological (MR) Fluid started to be used for industrial applications in the last 20 years, and, from that moment on, innovative uses have been evaluated for different applications to exploit its characteristic of changing yield stress as a function of the magnetic field applied. Because of the complexity of the behavior of the MR fluid, it is necessary to perform lots of simulations, combining multi-physical software capable of evaluating all the material’s characteristics.

The paper proposes a strategy capable of quickly verifying the feasibility of an innovative MR system, considering a sufficient accuracy of the approximation, able to easily verify the principal criticalities of the innovative applications concerning the MR fluid main electromagnetic and fluid-dynamic capabilities. The procedure follows the main steps: 1. design the solution (functionally related to the MR principles); 2. steady-state analyses (performed respectively with Altair Flux and Altair Acusolve) needed for defining the electromagnetic and the fluid-dynamic behavior of the fluid application; 3. after the basic feasibility definition, material, and geometrical optimization are performed for maximizing the MR capabilities into the innovative system design.

The proposed strategy has been used to validate the feasibility analysis of a Magneto-Rheological Brake for automotive applications, particularly for electric vehicles. Once the design phase defines a preliminary functional geometry for the application taken into consideration, it is needed to validate (through software analysis) the effectiveness of the innovative layout and its capabilities to reach the expected results, before developing a prototype that requires an important economical effort.
Next Generation Seat Ventilation System for Genesis EV
Authors: Jeong Dongwoo , Lee Seungyoung , Kim Sangho , Choi Byungyong , Park Sangdo , Kang Taeuk , Kim YunHo , Lim Hosub
Published: April 2023

The shift towards electric vehicles is gaining pace to address carbon neutrality and environmental concerns. New technologies are being developed to cater to the unique features of EVs, such as the low indoor noise at low speeds, which require a low-noise ventilation system. A new dual-blower type system was developed to solve the problem of seat-bottom package caused by battery placement in the vehicle. This system uses two blowers, one for the cushion and one for the back, and reduces RPM to lower high-frequency noise. A new solution was introduced for temperature drop performance in the ventilation system. An integrated controller was also developed to control the seat warmer and ventilation system, with a smart control function added to respond to vehicle speed and ventilation time based on customer usage. As a result, this new ventilation system improves air volume, reduces noise, improves foot space, and reduces the number of parts compared to the previous system.
Effects of Sequential Turn Signals under Realistic Visual Conditions
Authors: Flannagan Michael , Waragaya Takeshi , Kita Yasushi
Published: April 2023

Sequential turn signals are becoming more common, partly because of the availability of the detailed temporal and spatial control of light that is allowed by LED sources. They seem to be popular with drivers, and some human factors considerations suggest that they may more effectively convey information about intended maneuvers. This research was designed to investigate possible benefits by presenting experimental participants with a variety of sequential and static turn signals under realistic field conditions. The experimental tasks were based on possible encounters at four-way intersections. Passenger cars were statically positioned to represent such encounters. Participants were seated in one of the vehicles and were asked to make simple but meaningful judgments about intended turns by the other vehicles. Visual conditions were realistic in terms of the viewing geometry and photometry. Experiments were conducted in the day and at night. Three experiments were performed. In two of the three experiments there were statistically significant preferences for sequential turn signals over static turn signals in subjective ratings, but comparisons between sequential and static turn signals in objective measures were not statistically significant in any of the three experiments.
Investigation of Horizontal Light Function Positions on the Distance Estimation by Test Persons to Ensure Road Safety
Authors: Hinterwaelder Christian , Kobbert Jonas , Kruppa Michael , Hamm Michael
Published: April 2023

When designing new vehicles, the legal requirements of the countries in which the vehicles are homologated must be observed and implemented. The manufacturers try to consider the legal framework of the UN-ECE (United Nations Economic Commission for Europe), CCC (China Compulsory Certification) and FMVSS (Federal Motor Vehicle Safety Standard) 108 in the same vehicle to keep the variance low. For the appearance of the vehicle, the position of the light modules in the front of the vehicle is important. In addition to the surface requirements of lighting functions, the positions of the low beam (LB), high beam (HB) and the position of daytime running lights (DRL) are also regulated. When it comes to these mounting positions, the legislation between the US and the EU differs quite significantly. The UN-ECE legal framework does not describe the distance between the left and right Adaptive Front Lighting System with a certain value, but only requires the distance to the outer edge of the vehicle to be less than 400 mm. The FMVSS 108 on the other hand stipulates, that the distance should be "as far apart as practicable". The underlying reason for that is, that the distance and width from oncoming traffic could be misjudged if the low beam is placed too far inboard of the vehicle instead of to the outer edges. For this reason, with the support of a test person study, this paper examines different horizontal mounting positions of low beam in combination with several light setup positions, to investigate the impact of the headlight position on the distance assessment. The results can be used to design future cars in such a way that innovative design can be implemented while ensuring road safety.
Design Improvement of Frame Structure through MBD Simulations to Reduce Handle Bar Vibrations in 2-Wheeler (Scooters)
Authors: Sharma Ankush , Kaka Vaibhav
Published: April 2023

Harshness performance is a key aspect within ride comfort assessment for any vehicle. In this paper, by means of multibody dynamics simulation analysis, harshness performance of a scooter felt at the handle bar was examined. The term “Harshness” has been used here in analogy to excessive vibrations felt at handle bar. The vehicle was modeled in VI-Motorcycle & simulated on a virtual track. Accelerations were also measured on physical vehicle & FFT’s trend of the same were correlated through simulation. Various frame design proposals were simulated for harshness improvement & final frame configuration showing improvement considering design feasibility was proposed. Final configuration was also tested in a physical vehicle & performance improvement was validated. Details of modeling, physical testing, data analysis & suggested amendments are stated in relevant sections of this paper.
Review on CAN Bus Protocol: Attacks, Difficulties, and Potential Solutions
Authors: Appajosyula Kalyan Sai Vital Vamsi , Pacharla Sreedhar Reddy
Published: April 2023

The new generation vehicles these days are managed by networked controllers. A large portion of the networks is planned with more security which has recently roused researchers to exhibit various attacks against the system. This paper talks about the liabilities of the Controller Area Network (CAN) inside In-vehicle communication protocol and a few potentials that could take due advantage of it. Moreover, this paper presents a few security measures proposed in the present examination status to defeat the attacks. In any case, the fundamental objective of this paper is to feature a comprehensive methodology known as Intrusion Detection System (IDS), which has been a significant device in getting network data in systems over many years. To the best of our insight, there is no recorded writing on a through outline of IDS execution explicitly in the CAN transport network system. Therefore, we proposed a top-down examination of IDS through a write-up based on the following perspectives: Detection draws near, Organization systems, going after methods, and technical challenges. Likewise, it has additionally arranged the abnormality-based IDS as per the strategies stated below, i.e. Frequency-based, AI-based, measurable-based, and statistical-based strategies as a component.
Novel Distributed Control Architecture for Formula SAE-Type Electric Vehicles
Authors: Falco Samantha , Resalayyan Rakesh , Somiruwan Ayodhya , Singhabahu Chanaka , Hasnain Arafat , Khaligh Alireza
Published: April 2023

This paper proposes a new distributed/zonal control architecture composed of generic control modules. The new architecture increases the number of available input and outputs and improves reliability through redundancy, helping electric vehicles (EVs) meet the demand for advanced vehicle features and reliability. Each control module is equipped with analog and digital input pins, digital output pins, 2 CAN bus connections, power supplies from the 12V EV battery, a state-of-the-art DSP, and a wireless telemetry module for remote datalogging. A software architecture is developed to enable local signal processing from sensors, communication between modules in the distributed control architecture, and actuation of control objectives. Two CAN transceivers on two separate CAN busses are included for redundancy. Digi XBee Pro 900 HP module is used for long-distance wireless datalogging. TMS320F283874s microcontroller is used for its significant processing power and high number of peripherals. The controller units/boards were designed, fabricated and tested. Successful experimental validation was performed using the control module and emulator boards for the battery management system (BMS) and inverter. Multiple modules are connected and their ability to receive information from sensors, communicate with other boards, and control external hardware is tested. The prototype developed is intended for use in a Formula SAE EV.
Characterization and Modeling of Instrument Panel Textile Trim Materials for Passenger Airbag Deployment Analysis
Authors: G Karthigan , Savic Vesna , Hu Sibo , Ravichandran Gowrishankar , Tripathy Biswajit
Published: April 2023

Premium instrument panels (IPs) contain passenger airbag (PAB) systems that are typically comprised of a stiff plastic substrate and a soft ‘skin’ material which are adhesively bonded. During airbag deployment, the skin tears along the scored edges of the door holding the PAB system, the door opens, and the airbag inflates to protect the occupant. To accurately simulate the PAB deployment dynamics during a crash event all components of the instrument panel and the PAB system, including the skin, must be included in the model. It has been recognized that the material characterization and modeling of the skin tearing behavior are critical for predicting the timing and inflation kinematics of the airbag. Even so, limited data exists in the literature for skin material properties at hot and cold temperatures and at the strain rates created during the airbag deployment. This paper presents tensile test results of one typical skin material conducted at four different strain rates of 0.01/s, 1/s, 10/s, and 100/s. Challenges in testing are discussed. A material modeling methodology is proposed that accounts for anisotropy, loading rate sensitivity and failure, and is verified by comparison of results from simulation and physical tests. Finally, recommendations for setting proper contact parameters between different parts in the model and for proper representation of the adhesive between the instrument panel substrate and skin are presented.