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Sliding Mode Controlled Half Car Suspension System with Magnetorheological Damper

Anna University-AROCKIA SUTHAN SOOSAIRAJ, ARUNACHALAM K
  • Technical Paper
  • 2020-01-1540
To be published on 2020-06-03 by SAE International in United States
Attenuation of vibrations caused by the road undulance conditions are tedious and very much related to human health and vehicle handling problems. One of the promised approaches to solving these problems in a vehicle suspension system is the use of effective controllers. In this paper, the sliding mode controller (SMC) is designed and used to control the magnetorheological (MR) damper. The performance of the proposed controller is verified by incorporating the controller in a half car vehicle suspension model. In a suspension damper design, Modified Bouc-Wen model is used to characterize the hysteretic behaviour of MR damper parameters. The voltage control algorithm is used to convert the desired force into the varied voltage input to the MR damper. The fail-proof advantage of MR damper is analysed by comparing the results of uncontrolled MR suspension with a passive system. In order to limit the pitch angle and to achieve the improved ride comfort and stability of the vehicle, the vertical displacement of the front and rear body of the half-car model is controlled by the SMC…
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Formula SAE Data Acquisition and Detailed Analysis of a Lap

Georgia Southern University-Connor M. Ashford, Aniruddha Mitra
  • Technical Paper
  • 2020-01-0544
To be published on 2020-04-14 by SAE International in United States
Formula Society of Automotive Engineers (FSAE) International is a student design competition organized by SAE. The student design involves engineering and manufacturing a formula style racecar and evaluating its performance. Testing and validation of the vehicle is an integral part of the design and performance during the competition. At the collegiate level the drivers are at the amateur level. As a result, the human factor plays a significant role in the outcome of the dynamic events. In order to reduce the uncertainty factor and improve the general performance, driver training is necessary. Instead of overall performance of the driver based on individual lap, our current research focuses on the more detailed components of the driver’s actions throughout different sections of the lap. A complete lap consists of several components, such as, straight line acceleration and braking, max and min radius cornering, slalom or “S” movements, and bus stops or quick braking and turning. In order to evaluate the performance of each driver in each of these components, an AiM data acquisition system is mounted in…
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Bearing Fault Diagnosis of the Gearbox Using Blind Source Separation

Nanjing University of Science & Technology-Hong Zhong, Jingxing Liu, Liangmo Wang, Yang Ding, Yahui Qian
  • Technical Paper
  • 2020-01-0436
To be published on 2020-04-14 by SAE International in United States
Gearbox fault diagnosis is one of the core research areas in the field of rotating machinery condition monitoring. The signal processing-based bearing fault diagnosis in the gearbox is considered as challenging as the vibration signals collected from acceleration transducers are, in general, a mixture of signals originating from an unknown number of sources, i.e. an underdetermined blind source separation (UBSS) problem. In this study, an effective UBSS-based algorithm solution, that combines empirical mode decomposition (EMD) and kernel independent component analysis (KICA) method, is proposed to address the technical challenge. Firstly, the nonlinear mixture signals are decomposed into a set of intrinsic mode function components (IMFs) by the EMD method, which can be combined with the original observed signals to reconstruct new observed signals. Thus, the original problem can be effectively transformed into over-determined BSS problem. Then, the whitening process is carried out to convert the over-determined BSS into determined BSS, which can be solved by the KICA method. Finally, the ant lion optimization (ALO) is adopted to further enhance the performance of the EMD-KICA method.…
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Direct Yaw Moment Control of Electric Vehicle with 4 In-Wheel Motors to Improve Handling and Stability

China FAW Group Corporation-Jinlong Cui, Zehui Zhou, Yang Fang, Deping Wang, Tianqiang Zhang, Aibin Wu, Qichun Sun, Yang Zhao
College of Automotive Engineering Jilin University-Yongqiang Zhao
  • Technical Paper
  • 2020-01-0993
To be published on 2020-04-14 by SAE International in United States
More and more OEMs are interested in in-wheel-motor drive vehicles. One of the in-wheel-motor drive vehicle key technologies is multi-motor torque distribution. A direct yaw moment control strategy for torque distribution was introduced in this paper to improve 4 in-wheel-motor electric vehicle’s handling and stability. The control method consists of three components: feedback control based on target yaw rate, feedforward control based on current lateral acceleration and deceleration control based on under/oversteer situation. Feedback control is used to make vehicle’s real yaw rate following the driver’s target yaw rate and improve vehicle yaw rate response and stability. The target yaw rate is calculated by 2DOF vehicle model and limited by lateral acceleration and vehicle current steering condition. The feedforward control is used to increase the vehicle yaw rate gain and reduce the vehicle understeer characteristic when accelerating in a curve. The deceleration control can reduce the driving torque of each motor to slow down the vehicle when in critical steering condition. The proposed control strategy was verified by an in-wheel-motor drive electric vehicle test and…
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Impact of fuel octane quality on various advanced vehicle technologies

Shell Global Solutions (Deutschland)-Caroline Magdalene Zinser, Patrick Haenel
Shell Global Solutions (UK)-Alastair Smith
  • Technical Paper
  • 2020-01-0619
To be published on 2020-04-14 by SAE International in United States
Fuel with higher octane content is playing a key role in optimising engine performance by allowing a more optimal spark timing which leads to increased engine efficiency and lower CO2 emissions. In a previous study the impact of octane was investigated with a vehicle fleet of 20 vehicles using market representative fuels, varying from RON 91 to 100. The resulting data showed a clear performance and acceleration benefit when higher RON fuel was used. In this follow-up study 10 more vehicles were added to the database. The vehicle fleet was extended to be more representative of Asian markets, thus broadening the geographical relevance of the database, as well as adding vehicles with newer technologies such as boosted down-sized direct injection engines, or higher compression ratio engines. Eight different fuel combinations varying in RON were tested, representing standard gasoline and premium gasoline in different markets around the world. The new results augment our previously published octane study and result in a vehicle fleet dataset comprising 30 cars from 18 different automotive manufactures. Two key metrics were…
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Development and Application of a Collision Avoidance Capability Metric

AAA Northern California Nevada & Utah-Paul Wells, Atul Acharya
Dynamic Research Inc.-Jordan Silberling, Joseph Kelly, John Lenkeit
  • Technical Paper
  • 2020-01-1207
To be published on 2020-04-14 by SAE International in United States
This paper describes the development and application of a newly developed metric for evaluating and quantifying the capability of a vehicle/controller (e.g., Automated Vehicle or human driver) to avoid collisions in nearly any potential scenario, including those involving multiple potential collision partners and roadside objects. At its core, this Collision Avoidance Capability (CAC) metric assesses the vehicle’s ability to avoid potential collisions at any point in time. It can also be evaluated at discrete points, or over time intervals. In addition, the CAC methodology potentially provides a real-time indication of courses of action that could be taken to avoid collisions. The CAC calculation evaluates all possible courses of action within a vehicle’s performance limitations, including combinations of braking, accelerating and steering. Graphically, it uses the concept of a “friction ellipse”, which is commonly used in tire modeling and vehicle dynamics as a way of considering the interaction of braking and turning forces generated at the tire contact patches. When this concept is applied to the whole vehicle, and the actual or estimated maximum lateral and…
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A Smart Measuring System for Vehicle Dynamics Testing

Politecnico di Torino-Enrico Galvagno, Stefano Mauro, Stefano Pastorelli, Antonio Tota
  • Technical Paper
  • 2020-01-1066
To be published on 2020-04-14 by SAE International in United States
A fast measurement of the car handling performance is highly desirable to easily compare and assess different car setup, e.g. tires size and supplier, suspension settings, etc. Instead of the expensive professional equipment normally used by car manufacturers for vehicle testing, the authors propose a low cost solution that is nevertheless accurate enough for comparative evaluations. The paper presents a novel measuring system for vehicle dynamics analysis, which is based uniquely on the sensors embedded in a smartphone and completely independent on the signals available through vehicle CAN bus. Data from tri-axial accelerometer, gyroscope, GPS and camera are jointly used to compute the typical quantities analyzed in vehicle dynamics applications. In addition to signals like yaw rate, lateral and longitudinal acceleration, vehicle speed and trajectory, normally available when working with Inertial Measurement Units (IMU) equipped with GPS, in the present application also the steering wheel angle is measured by artificial vision algorithms that use the phone camera.. The latter signal, besides being important for identifying the maneuver imposed by the driver, it enables the usage…
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A Method for Simultaneous State of Charge, Maximum Capacity and Resistance Estimation of a Li-Ion Cell Based on Equivalent Circuit Model

Auburn University-Saurabh Gairola, Yang Hu
  • Technical Paper
  • 2020-01-1182
To be published on 2020-04-14 by SAE International in United States
Accurate estimation of the State of Charge (SOC), maximum capacity (Qmax) and internal resistance are critical for battery monitoring, i.e., determining the status, health, and performance figures of a battery. SOC is a key indicator of the instant status for battery systems, while Qmax and internal resistance are related to the capacity fade (SOHQ) and power fade (SOHP) respectively, which represent the abilities of a battery to store energy, retain charge over extended periods and provide the required power for acceleration, etc. Traditional methods using complex models and look-up tables have high computation requirements which makes them unsuitable for online applications. In this paper, we propose a simple method for simultaneous SOC, Qmax and internal resistance estimation based on a second-order equivalent circuit model (ECM). A Variable Model framework based Adaptive Extended Kalman filter (VM-AEKF) is implemented for joint SOC and model parameter estimation where the VM framework is designed specifically to improve the stability and accuracy of parameter estimation under conditions when the system is not sufficiently excited by the input signal. Simultaneously, a…
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Statistical Analysis of City Bus Driving Cycle Features for the Purpose of Multidimensional Driving Cycle Synthesis

University of Zagreb-Jakov Topić, Branimir Skugor, Josko Deur
  • Technical Paper
  • 2020-01-1288
To be published on 2020-04-14 by SAE International in United States
Driving cycles are typically defined as time profiles of vehicle velocity, and as such they reflect basic driving characteristics. They have a wide application from the perspective of both conventional and electric road vehicles, ranging from prediction of fuel/energy consumption (e.g. for certification purposes), estimation of greenhouse gas and pollutant emissions to selection of optimal vehicle powertrain configuration and design of its control strategy. In the case of electric vehicles, the driving cycles are also applied to determine effective vehicle range, battery life period, and charging management strategy. Nowadays, in most applications artificial certification driving cycles are used. As they do not represent realistic driving conditions, their application results in generally unreliable estimates and analyses. Therefore, recent research efforts have been directed towards development of statistically representative synthetic driving cycles derived from recorded GPS driving data. The state-of-the-art synthesis approach is based on Markov chains, typically including vehicle velocity and acceleration as Markov chain states. However, apart from the vehicle velocity and acceleration, a road slope and vehicle mass are also shown to significantly impact…
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Kalman Filter Slope Measurement Method Based on Improved Genetic Algorithm-Back Propagation

Wuhan University of Technology-Haoyu Wang, Donghua Guo, Gangfeng Tan, Zhenyu Wang, Ming Li, Yifeng Jiang, Meng Ye, Kailang Chen
  • Technical Paper
  • 2020-01-0897
To be published on 2020-04-14 by SAE International in United States
How to improve the measurement accuracy of road gradient is the key content of the research on the speed warning of commercial vehicles in mountainous roads. The large error of the measurement causes a significant effect of the vehicle speed threshold, which causes a risk to the vehicle's safety. Conventional measuring instruments such as accelerometers and gyroscopes generally have noise fluctuation interference or time accumulation error, resulting in large measurement errors. To solve this problem, the Kalman filter method is used to reduce the interference of unwanted signals, thereby improving the accuracy of the slope measurement. However, the Kalman filtering method is limited by the estimation error of various parameters, and the filtering effect is difficult to meet the project research requirements. In this paper, the acceleration of vehicle gravity, driving speed and acceleration of parallel slope are utilied as auxiliary measurement parameters to improve the measurement method. Based on the Kalman model, GA (genetic algorithm) and BP (Back Propagation) neural network are employed to carry out the innovation, covariance matrix and the last Kalman…