Road Load Data Research Articles

Performance Verification and Evaluation of Semi-Active Actuator System Using Quarter Car Lab Simulation with RLDA Data

This study outlines a methodology for determining the durability specifications of electronically controlled dampers by examining performance degradation observed on actual driving roads. It identifies areas of performance decline and the primary causes affecting major actuator dampers. Traditionally, the durability performance of automobile parts has been assessed by calculating damage based on load profiles. However, analyzing actual road conditions is essential because the control commands of electronically controlled suspension systems change in real time according to load conditions. Simulations based on Road Load Data Acquisition (RLDA) use statistically independent representative road surfaces to assess damper deterioration performance. Following this analysis, a rig test of the damper is performed to establish the durability specifications for damper actuator products. The primary form of performance degradation observed was a change in the tensile damping force, which was more substantial than the degradation observed on the compression side. Oil leakage and cavitation were identified as significant influencing factors from a Failure Mode and Effects Analysis (FMEA) perspective. The study concludes that additional design research is necessary, focusing on damper oil and leakage, while also considering the control algorithm’s effects in designing electronically controlled dampers.

Effect of Suspension Preload on Fatigue Life of Two Wheeler Frame

A suspension unit is a significant component in a vehicle. It provides a smooth ride, improves traction, maintains ride geometry and facilitates better handling. A typical suspension setup in a two-wheeler consists of a front and rear suspension setup working independently to achieve the desired function. It connects the wheel to the chassis of the vehicle, transferring road load and hence affecting the durability of the structural members. This research work focuses on the durability aspect of the suspension unit with its preload as the control parameter. A rear suspension with seven preload settings was chosen for this study. The provision requirements of preload settings in suspension were experimentally analyzed using static measurements. The vehicle was instrumented with transducers (strain gauges, accelerometers, linear displacement sensors, and Global Positioning System (GPS) sensors), and dynamic road load data was acquired at different rear suspension preload settings by changing from the minimum, i.e., the 1st setting, to the maximum, i.e., the 7th setting, while keeping other parameters constant. Statistical analysis and fatigue analysis were utilized to study the dynamic effects. It was observed and quantified that increasing the preload for higher static load conditions or rough road conditions provides a smoother ride and improved life due to lower bump stopper engagement and full bump conditions owing to increased compression stroke availability. Keywords: Suspension, Fatigue Life, Stiffness, Riding, Strain Gauges

A relationship between vehicle coastdown performance metrics and fuel efficiency

In contemporary times, societal and legal institutions are earnestly committed to mitigating carbon dioxide (CO2) emissions into the atmosphere, thereby averting global warming. The automotive industry mirrors this commitment, necessitating the development of vehicles characterized by heightened energy efficiency. Such vehicles should boast an extended range while minimizing fuel consumption and CO2 emissions. A pivotal aspect in vehicle development involves the early determination of fuel economy (FE), contingent upon the projected characteristics of the vehicle and its intended market positioning with regard to fuel economy. Over time, diverse methodologies for calculating FE have emerged. These include hybrid regression models incorporating key input variables such as instantaneous vehicle speed and acceleration measurements, theoretical approximation methods derived from the physical properties of engine-vehicle systems, correlations among traffic-related parameters, power-demand models, as well as artificial neural networks and genetic algorithms. These approaches leverage various vehicle input data, encompassing engine speed, torque, fuel flow, intake manifold mean temperature, make of the car, engine style, weight of the car, vehicle type, transmission system type, and other relevant factors. Regrettably, the literature lacks a straightforward and expeditious means of estimating FE for a group of analogous vehicles, a deficiency addressed by the present work. The proposed empirical physical model facilitates FE estimations for a vehicle using a parsimonious set of input information: engine displacement, performance (recovery speed times), and road load data. These inputs are subjected to mathematical parameter adjustments within the empirical model. To validate the efficacy of this approach, the empirical model is applied in a Brazilian case study. The results attest to the success of the method, demonstrating a margin of error within 6% when compared to the official Brazilian government public data for the tested vehicle, particularly in the contexts of city and highway cycles.

A 4750 hours’ durability investigation of the PEMFC stack based on fuel cell hybrid vehicles conditions

ABSTRACT A novel protocol for testing the durability of proton exchange membrane fuel cell (PEMFC) stacks is developed using real-world road load data obtained from automobiles equipped with a PEMFC system manufactured by Weichai Power Company Limited, and the predetermined methodology is carried out for a cumulative duration of 4750 hours. The empirical results obtained from the durability test reveal that the average cell voltages (ACV) at specific current of 21 A, 105 A, 175 A, and 290 A exhibit degradation rates of 2%, 3.3%, 3.9%, and 10.9%, correspondingly. Furthermore,the polarization curve test results demonstrate ACV decay rates of 2.2% and 6.9% at 21 A and 360 A, respectively. The output voltage decay increases and the consistency of cells diminishes as the current rises. In comparison to the initial stage of the durability test, there is a slight decline in cell consistency observed toward the conclusion. In addition, a sensitivity test of the operational conditions is conducted at the 50th and 500th cycles, respectively. The findings reveal that the sensitivity to the cell consistency and output voltage remains largely stable throughout the durability test, and this suggests that the stack does not exhibit any noticeable alterations in its physicochemical characteristics.

Feasibility Study of Wheel Torque Prediction with a Recurrent Neural Network Using Vehicle Data

In this paper, we present a feasibility study on predicting the torque signal of a passenger car with the help of a neural network. In addition, we analyze the possibility of using the proposed model structure for temperature prediction. This was carried out with a neural network, specifically a three-layer long short-term memory (LSTM) network. The data used were real road load data from a Jaguar Land Rover Evoque with a Twinster gearbox from GKN. The torque prediction generated good results with an accuracy of 55% and a root mean squared error (RMSE) of 49 Nm, considering that the data were not generated under laboratory conditions. However, the performance of predicting the temperature signal was not satisfying with a coefficient of determination (R2) score of −1.396 and an RMSE score of 69.4 °C. The prediction of the torque signal with the three-layer LSTM network was successful but the transferability of the network to another signal (temperature) was not proven. The knowledge gained from this investigation can be of importance for the development of virtual sensor technology.

Effect of Different Types of Electric Drive Units on the Energy Consumption of Heavy Commercial Electric Vehicles

The increasing demand for electric vehicles (EVs) in the transportation industry, especially for efficient battery–electric trucks, has led to an increase in studies on the efficiency or energy consumption of commercial vehicles. In this paper, average energy consumption was investigated in terms of the effect of different transmission types in vehicle models considering three routes, and the effect of the number of gears on energy consumption for each transmission type was analyzed. Target performance specifications and packaging were also evaluated. The optimal design could be identified in terms of transmission type, the number of gears, vehicle performance, and packaging. Vehicle models with two types of electric drive units (EDUs) were developed in a MATLAB/Simulink environment. Driving cycles were obtained from collected road load data of municipal, intercity, and regional areas operated by heavy-duty trucks using nCode software. The battery model was developed based on the electric circuit network (ECN) modeling technique. The main research purpose of this study was to investigate the effect of multispeed and multimodal EDUs and the number of gears on the energy consumption of heavy commercial electric vehicles from actual road conditions in Turkey. The three-speed EDU was the optimal design, providing 7.83, 7.26, and 7.21% less energy consumption on the three routes, compared with three-mode electric drive units. Consequently, the energy consumption difference was 7.5% for combined real road conditions.

Development of Test Cycle for Centrifugal Clutch of CVT Driven Scooters Intended for Urban Traffic Conditions

The present study deals with the development of a test cycle for the centrifugal clutch of continuously variable transmission (CVT) driven scooters. Centrifugal clutch experiences different duty cycles during the usage of scooters in city traffic and highways during its lifetime. Since the friction characteristics of the centrifugal clutch are controlled by acquired factors, it is difficult to predict ideal friction characteristics under all conditions. The wear of friction lining increases due to heat generated in the clutch assembly because of the repeated “stick-slip” phenomena. Therefore, an attempt has been made for developing à new test cycle by keeping the engagement frequency as a reference. Road load data for three different riding conditions have been collected and analyzed. The developed test cycle has been automated on the centrifugal clutch test bench and a new set of clutch liners was tested thoroughly. The surface roughness, thickness, and wear of clutch liners have been observed and evaluated against the field vehicles. For the surface roughness, maximum deviations of 3.74%, 3.36%, and 2.16% have been observed for trailing, middle and leading sections of clutch liners respectively. For the thickness, maximum deviations of 3.06%, 2.59%, and 3.14% have been observed for trailing, middle and leading sections of clutch liners respectively. The developed test cycle demonstrates a good correlation with field use.

Towards A Better Understanding Of Mechanical Stress Applied By Passenger Vehicle Customers With Optimized Instrumentation And Relevant Data Post-Processing Methodologies

The various mechanical parts of a vehicle must be designed to ensure a target level of reliability compatible with safety objectives while limiting oversizing. This requires automobile manufacturers to implement the relevant methodological tools adapted to the component failure mechanisms. Several improvements have been made over the past 10 years on this topic, in particular with tools taking into account the local properties of materials and thus delivering local stresses and damage at any point of each part. These procedures require track measurements or virtual road load data representing the image that each manufacturer chooses to have of a given customer severity level. This arbitrary level of severity then makes it possible to express a target performance threshold of the component to guarantee objective reliability. The difficulty in these methods is to be able to capture the severity levels of customers all over the world, which is by definition very variable because depending on several inputs like the road geography and quality, the customer behavior and style.The objective of this paper is to share the state-of-the-art methodologies implemented by PSA Groupe (now Stellantis) to capture this information with the best efficiency and also to reduce its cost through a Big Data approach.Three main themes will be addressed:○ Instrumentation strategy○Sampling methodology to catch the reality of the customer’s field○ Objectification and classification of customer life situations

Multi-body simulation with notch stress analysis of an axle assembly

The optimization of mining vehicle rear axle weld joints is a complex procedure. The designs for low-cycle fatigue with peak loads were analyzed using computational models and rig testing. On-road evaluation of high-cycle fatigue was performed with the entire vehicle. The iterative analysis is used in design optimization to minimize design cycle time. In sophisticated fatigue calculations with all affecting factors, FEM is utilized. In fatigue failures using road load data, the present deterministic method yields up to 80% correlations. Some critical failure spots were most likely missed owing to operational variations caused by the randomness and multiaxiality of load transfer in link mechanisms with non-linear elements. The fabricated rear axle housing joints are optimized by comparing damage state estimates using stochastic type and multiaxial equivalent loads obtained using Multibody Simulation. The damage state analysis as MBS input stimulus in FE weld models and bolted designs were compared.

Improvement of Rear Seat Vibrations of Passenger Bus by Tuning Damper Characteristics

<div class="section abstract"><div class="htmlview paragraph">Passenger vehicles are used as one of the frequently used and versatile mode of transport. Commercial buses cater to short to long distance travel for city as well as highway applications. Thus, passenger ride comfort becomes paramount for the salability of the vehicle. Generally, it is observed that the rear seat experiences the worst ride comfort characteristics due to rear overhang and pitching characteristics of buses. Therefore the objective of this project is to improve the rear seat vibrations of passenger bus by tuning damper characteristics. Shock absorbers, being a low cost and easily interchangeable component is tuned first before optimizing other suspension parameters. The methodology is as follows: first, a 4 degree of freedom mathematical model is created on MATLAB Simulink R2015a environment. Time domain data is obtained by road load data analysis and used as an input for the mathematical model. An experimentation was carried out on the bus at speeds of 20 km/h over a single hump to obtain actual acceleration time domain data. The model is then correlated with actual test over a single hump.</div><div class="htmlview paragraph">After setting up baseline results, tuning of damper is carried out. First low speed compression range is tuned to obtain better ride comfort characteristics over Class A road and results are observed. This is done by varying the damping force from 5kgf to 100kgf in speeds between 0.05 m/s to 0.25 m/s in compression. Thereafter, high speed rebound range is tuned over a single hump by varying the damping force between 1000 kgf to 4000 kgf in speeds between 1m/s to 3 m/s in rebound travel and results are obtained. Finally, fitment of data in Ride Comfort Index is carried out as per ISO 2631. Therefore a comprehensive and parametric damper tuning sheet is prepared considering the natural frequency, critical damping coefficient and damping ratio.</div></div>

Method of reconstructing dynamic load characteristics for durability test Indexed by: of heavy semitrailer under different road conditions

The aim of the article is to present and validate a methodology for collecting road load data on a vehicle, driving on roads and analysis of a drive data signal under the wheel in the time domain, using FRF (Frequency Response Function) and the MTS 320 eight-poster inertia reacted road simulator. The elaborated drive data, was used to control the actuators forcing the movements of the wheels and the coupling part of the semi-trailer during durability tests. The road tests were carried out by registering physical variables in the time domain, by a set of sensors mounted on a vehicle. The data was collected from roads categorized as motorways, national and local roads. Differences between the variability of the parameters, collected on the roads and the variability of the drive data under the wheel, were determined for the particular types of roads, for loaded and unloaded vehicle. The obtained accuracy of reconstruction of the road load data conditions was as high as 97%. Therefore, the proposed method is suitable for reliable durability tests with use of the road simulator.

Realistic Correlation of Damage Estimate in Axle Housing of Commercial Vehicles Using Road Load Data with Bench Testing Results and Failure Analysis to Overcome Hot Forming Losses

Realistic Correlation of Damage Estimate in Axle Housing of Commercial Vehicles Using Road Load Data with Bench Testing Results and Failure Analysis to Overcome Hot Forming Losses

CAE analysis and road load data acquisition experimentation on bogie bracket of heavy duty commercial vehicle

Bogie bracket is a unit of suspension system in heavy-duty trucks. This part has been identified as critical component. Computer aided engineering (CAE) simulation software has been used for stress analysis and the forces influencing the failure of part. Stress concentration factor has been found in every zone of the bracket and the weaker sections have been identified in three iterations. The rough road (RR) and mining road (MR) were taken for critical analysis. Road load data acquisition (RLDA) test was conducted to validate the CAE. Six pairs of bogie brackets were tested on RR and MR test track conditions. Strain was measured through strain gauge. Hair crack failure was detected at weaker sections and eventual sudden failure was observed in six pairs of samples under RR and MR. In RR condition, cobblestone and MR condition, kutcha road caused higher rate of failure.

Failure Assessment of Load-Stabilizing Rod in Heavy-Duty Truck Through CAE and Testing in Rough Road Conditions

The load-stabilizing (LS) rod is a part of heavy-duty mining vehicle front axle suspension system. The application of LS rod is essential in mining vehicle used predominantly for transportation of iron ore, coal, etc. from stockpile to storage yard. In this vehicle, two front axles are used for higher load capacity and better maneuverability. The load-stabilizing rod is one of the most critical components to support and stabilize the load between the two front axles. Computer-aided engineering (CAE) simulation has been used for stress analysis to evaluate the various forces influencing the failure of LS rod. Failure analysis is carried out for different rough road (RR) conditions. Road load data acquisition is conducted to validate the CAE results. Five sets of load-stabilizing rods were tested on different road test tracks in RR conditions. Strain gauges are used to measure the maximum stresses and tensile force induced in the LS rod. Fracture failure has been detected at the weaker section in the LS rod.

Failure mode investigation and re-design of heavy-duty commercial vehicle bogie bracket

Heavy-duty commercial vehicles play a significant role in commodity logistics. For each of these vehicles, the suspension is the most essential system to support the load and road shock. Bogie type suspension system is employed to safeguard the vehicle from road shock. The bogie bracket is a juncture between the chassis and the axle in the suspension system. The bogie bracket has been identified as a critical part of the suspension system. In the present study, bogie bracket base design and modelling was performed using computer-aided engineering (CAE). The strength of the bogie was tested to identify weaker sections. Design modifications were performed to improve the strength on identified critical sections through reinforcement techniques. A road load data acquisition (RLDA) test was conducted under different road conditions to validate CAE results. Five different rough-road road surfaces were chosen for RLDA testing. Using strain gauges, strain data were acquired during the test. Corresponding stress values were obtained and maximum stress was found in all driving conditions. For the base design bogie bracket, under RLDA test, crack initiation and crack propagation were identified under vertical loads. A reinforced bogie bracket was designed and found to have a higher strength and longer expected life than that of the base design.

Real World Fuel Consumption and Emissions From LDVs and HDVs

Real world emission and energy consumption behavior from vehicles is a key element for meeting air quality and greenhouse gas (GHG) targets for any country. While CO2 fleet targets for vehicles are defined on basis of standardized test procedures, in real driving conditions manifold parameters show large variabilities. Main differences are Driving cycle Vehicle loading and driving resistances Ambient temperature levels, start conditions and trip length Gear shift behavior of the drivers Power demand from auxiliaries Fuel quality For the upcoming update of the Handbook Emission Factors for Road Transport (HBEFA 4.1) we have performed analysis, measurements and simulations to elaborate real world energy consumption values for 2-wheelers, passenger cars (PC), light commercial vehicles (LCVs) and heavy duty vehicles (HDVs), so called emission factors (EF). EFs show fuel consumption or emission level in [g/km] and [#/km] for fuel, gaseous exhaust gas components and also for the particle number (PN). EFs are provided for a lot of different traffic situations covering stop & go up to highway for different road gradient categories. EFs are different for each vehicle category and for each powertrain technology and emission standard (from EURO 0 gasoline PC to EURO VI HDV with CNG engine). To produce the EFs, vehicle tests from chassis dyno and from on-board measurements were collected in all European labs to set up models for all vehicle segments in the passenger cars and heavy duty emission model (PHEM). The models for PC and LCVs were based on weight and road load data available from the type approval test, the worldwide harmonized light vehicles test procedure (WLTP), and then calibrated in a stepwise approach to consider all influences in real world driving. Finally, the results for new vehicle fleet fuel consumption values were compared with data from the fuel consumption monitoring data base. For HDVs, the models are based on data from the development of the HDV CO2 determination method (Regulation (EU) 2017/2400, “VECTO”). The methods and also the results in terms of differences between real world and type approval for loading, road load, energy consumption and emission levels are described in this paper.

A Simulation Approach for Identification and Design Optimization to Prevent Headrest Rattle

<div class="section abstract"><div class="htmlview paragraph">Squeak and rattle concerns account for approximately 10% of overall vehicle Things Gone Wrong (TGW) and are a major quality concern for automotive OEM’s. Seat is one of the major contributors of squeak and rattle issues observed in customer verbatim. Seat head rest rod and bezel are designed concentric to each other with a gap that allows free movement and a locking pin to position at different levels. Due to the design gap and weight of the head rest there is always tendency for relative displacement leading to rattle issues. Seat headrest, is close to the customer ear and any rattles at headrest will create annoying driving experience. Also, the contradictory requirements between efforts and rattle makes the scenario more difficult to fine tune the bezel specifications. The root cause for head rest rattle issues can also be related to free play between bezel and seat frame, free play between bezel and cap, looseness between locking pin and headrest rod etc. Identification of issue at physical testing is common practice subject to availability of test sample and road load data. Also, source identification and modification comes at the later part of the project. This paper establishes a process to perform the head rest rattle analysis by utilizing existing FE techniques. The FE analysis is performed using SNRD software available in hyper works platform. An older program seat FE model is built and validated with experimental results. Also, relative displacement measured between the headrest rod and bezel are correlated well with the simulation results. The occurrence and severity of rattle can be understood when the relative displacement is more than the design gap. Also, root cause analysis is performed by modal contribution analysis which gives an option for design sensitivity studies and compare relative displacements of different designs. The proposed methodology using FE techniques can help in identifying head rest rattle issues at early design stage.</div></div>

CAE analysis and road load data acquisition on bogie bracket of heavy duty commercial vehicle

CAE analysis and road load data acquisition on bogie bracket of heavy duty commercial vehicle

Generation of Artificial Road Profile for Automobile Spring Durability Analysis

This paper presents the use of a generated artificial road profile in the simulation of a quarter car model for spring durability based-force extraction. In situ measurement of the road loading profile for automotive spring durability analysis, requires considerable cost and effort due to the complex experimental setup. Hence, an artificial road profile was generated for the quarter car model simulation to obtain the spring force signals. Initially, according to the ISO 8608 standard, a class “A” artificial road profile was generated using a designated waviness value, unevenness index and random phase angle. The generated road profile was used as the input to a constructed quarter car model to obtain the spring force signals. Subsequently, the generated nominal force signal was used to predict the fatigue life of the spring. Moreover, to obtain the localise fatigue behaviour of the spring, a finite element spring model together with the force signal was used for fatigue prediction. Under this class “A” road excitation, the spring possessed very high fatigue life of 1.87 × 106 blocks to failure. Further, a series of spring variant was analysed for fatigue life through this road class excitation. The relationship between spring stiffness and fatigue lives established using power regression and the coefficient of determination (R2) as high as 0.9815 was obtained. Therefore, this analysis will assist in automobile spring design regarding fatigue when road load data is not available.

Wheel Hub Fatigue Performance under Non-constant Rotational Loading and Comparison to Eurocycle Test

Wheel Eurocycle (EC) loading condition could be adapted to hub as a result of similar loading characteristics on vehicle. A correlation is constructed between road load data (RLD) for specified vehicles and EC test spectrum. To provide correlation between EC and RLD, test speed, axial and lateral loads at EC are converted to cyclic loading condition and relevant loading scenarios are generated. Rotational effect is taken into account. Pseudo-damage results of RLD and EC spectra are compared and expected fatigue lifetime for hub is presented.