Fuzzy Estimation of Vehicle Speed

2005 ◽  
Author(s):  
Kyeung Heub Oh ◽  
Jin Kwon Hwang ◽  
Chul Ki Song
Keyword(s):  
Estimation Method ◽  
Experimental Result ◽  
Vehicle Speed ◽  
Wheel Slip ◽  
Worst Case ◽  
Acceleration Signal ◽  
Vehicle Velocity ◽  
Antilock Braking System ◽  
Speed Estimator ◽  
Using Data

The absolute longitudinal speed of a vehicle is estimated by using data from an accelerometer of the vehicle and wheel speed sensors of a standard 50-tooth antilock braking system. An intuitive solution to this problem is, “When wheel slip is low, calculate the vehicle velocity from the wheel speeds; when wheel slip is high, calculate the vehicle speed by integrating signal of the accelerometer.” The speed estimator weighted with fuzzy logic is introduced to implement the above concept, which is formulated as an estimation method. And the method is improved through experiments by how to calculate speed from acceleration signal and slip ratios. It is verified experimentally to usefulness o estimation speed of a vehicle. And the experimental result shows that the estimated vehicle longitudinal speed has only a 6 % worst-case error during a hard braking maneuver lasting a few seconds.

scholarly journals A Novel Longitudinal Speed Estimator for Four-Wheel Slip in Snowy Conditions

2021 ◽  
Vol 11 (6) ◽  
pp. 2809
Author(s):  
Dongmin Zhang ◽  
Qiang Song ◽  
Guanfeng Wang ◽  
Chonghao Liu
Keyword(s):  
Control Strategies ◽  
Low Cost ◽  
Estimation Error ◽  
Slip Rate ◽  
Vehicle Speed ◽  
Acceleration Sensor ◽  
Wheel Slip ◽  
Longitudinal Acceleration ◽  
Tire Rotation ◽  
Speed Estimator

This article proposes a novel longitudinal vehicle speed estimator for snowy roads in extreme conditions (four-wheel slip) based on low-cost wheel speed encoders and a longitudinal acceleration sensor. The tire rotation factor, η, is introduced to reduce the deviation between the rotation tire radius and the manufacturer’s marked tire radius. The Local Vehicle Speed Estimator is defined to eliminate longitudinal vehicle speed estimation error. It improves the tire slip accuracy of four-wheel slip, even with a high slip rate. The final vehicle speed is estimated using two fuzzy control strategies that use vehicle speed estimates from speed encoders and a longitudinal acceleration sensor. Experimental and simulation results confirm the algorithm’s validity for estimating longitudinal vehicle speed for four-wheel slip in snowy road conditions.

scholarly journals Estimation of resistance force at steady-state sinkage for cylindrical wheel-typed lunar/planetary exploration rovers with function of push–pull locomotion

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Daisuke Fujiwara ◽  
Naoki Tsujikawa ◽  
Tetsuya Oshima ◽  
Kojiro Iizuka
Keyword(s):  
Steady State ◽  
Estimation Method ◽  
Planetary Exploration ◽  
Experimental Result ◽  
Resistance Force ◽  
Estimation Model ◽  
Loose Soil ◽  
Key Factor ◽  
The Relationship ◽  
Resistance Forces

Abstract Planetary exploration rovers have required a high traveling performance to overcome obstacles such as loose soil and rocks. Push-pull locomotion rovers is a unique scheme, like an inchworm, and it has high traveling performance on loose soil. Push-pull locomotion uses the resistance force by keeping a locked-wheel related to the ground, whereas the conventional rotational traveling uses the shear force from loose soil. The locked-wheel is a key factor for traveling in the push-pull scheme. Understanding the sinking behavior and its resistance force is useful information for estimating the rover’s performance. Previous studies have reported the soil motion under the locked-wheel, the traction, and the traveling behavior of the rover. These studies were, however, limited to the investigation of the resistance force and amount of sinkage for the particular condition depending on the rover. Additionally, the locked-wheel sinks into the soil until it obtains the required force for supporting the other wheels’ motion. How the amount of sinkage and resistance forces are generated at different wheel sizes and mass of an individual wheel has remained unclear, and its estimation method hasn’t existed. This study, therefore, addresses the relationship between the sinkage and its resistance force, and we analyze and consider this relationship via the towing experiment and theoretical consideration. The results revealed that the sinkage reached a steady-state value and depended on the contact area and mass of each wheel, and the maximum resistance force also depends on this sinkage. Additionally, the estimation model did not capture the same trend as the experimental results when the wheel width changed, whereas, the model captured a relatively the same trend as the experimental result when the wheel mass and diameter changed.

scholarly journals Design, Analysis and Application of Single-Wheel Test Bench for All-Electric Antilock Braking System in Electric Vehicles

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1294
Author(s):  
Xiangdang XUE ◽  
Ka Wai Eric CHENG ◽  
Wing Wa CHAN ◽  
Yat Chi FONG ◽  
Kin Lung Jerry KAN ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Test Bench ◽  
Potential Candidate ◽  
Vertical Force ◽  
Abs Algorithms ◽  
Braking System ◽  
Vehicle Velocity ◽  
Antilock Braking System ◽  
Antilock Braking ◽  
Electromechanical Brake

An antilock braking system (ABS) is one of the most important components in a road vehicle, which provides active protection during braking, to prevent the wheels from locking-up and achieve handling stability and steerability. The all-electric ABS without any hydraulic components is a potential candidate for electric vehicles. To demonstrate and examine the all-electric ABS algorithms, this article proposes a single-wheel all-electric ABS test bench, which mainly includes the vehicle wheel, the roller, the flywheels, and the electromechanical brake. To simulate dynamic operation of a real vehicle’s wheel, the kinetic energy of the total rotary components in the bench is designed to match the quarter of the one of a commercial car. The vertical force to the wheel is adjustable. The tire-roller contact simulates the real tire-road contact. The roller’s circumferential velocity represents the longitudinal vehicle velocity. The design and analysis of the proposed bench are described in detail. For the developed prototype, the rated clamping force of the electromechanical brake is 11 kN, the maximum vertical force to the wheel reaches 300 kg, and the maximum roller (vehicle) velocity reaches 100 km/h. The measurable bandwidth of the wheel speed is 4 Hz–2 kHz and the motor speed is 2.5 Hz–50 kHz. The measured results including the roller (vehicle) velocity, the wheel velocity, and the wheel slip are satisfactory. This article offers the effective tools to verify all-electric ABS algorithms in a laboratory, hence saving time and cost for the subsequent test on a real road.

Constrained and Unconstrained Partial Adjacent Category Logit Models for Ordinal Response Variables

2015 ◽  
Vol 47 (2) ◽  
pp. 169-206 ◽  
Author(s):  
Andrew S. Fullerton ◽  
Jun Xu
Keyword(s):  
General Social Survey ◽  
Estimation Method ◽  
Logit Models ◽  
Proportional Odds ◽  
Social Survey ◽  
Partial Model ◽  
Ordinal Response ◽  
Proportional Odds Assumption ◽  
Using Data ◽  
Response Variables

Adjacent category logit models are ordered regression models that focus on comparisons of adjacent categories. These models are particularly useful for ordinal response variables with categories that are of substantive interest. In this article, we consider unconstrained and constrained versions of the partial adjacent category logit model, which is an extension of the traditional model that relaxes the proportional odds assumption for a subset of independent variables. In the unconstrained partial model, the variables without proportional odds have coefficients that freely vary across cutpoint equations, whereas in the constrained partial model two or more of these variables have coefficients that vary by common factors. We improve upon an earlier formulation of the constrained partial adjacent category model by introducing a new estimation method and conceptual justification for the model. Additionally, we discuss the connections between partial adjacent category models and other models within the adjacent approach, including stereotype logit and multinomial logit. We show that the constrained and unconstrained partial models differ only in terms of the number of dimensions required to describe the effects of variables with nonproportional odds. Finally, we illustrate the partial adjacent category logit models with empirical examples using data from the international social survey program and the general social survey.

Adaptive calibration of Diesel engine injection for minimising fuel consumption with constrained NOx emissions in actual driving missions

2020 ◽  
pp. 146808742091880
Author(s):  
José Manuel Luján ◽  
Benjamín Pla ◽  
Pau Bares ◽  
Varun Pandey
Keyword(s):  
Diesel Engine ◽  
Fuel Consumption ◽  
Time Window ◽  
Transition Probability ◽  
Estimation Method ◽  
Engine Performance ◽  
Driving Cycle ◽  
Vehicle Speed ◽  
Adaptive Calibration ◽  
Emission Limits

This article proposes a method for fuel minimisation of a Diesel engine with constrained [Formula: see text] emission in actual driving mission. Specifically, the methodology involves three developments: The first is a driving cycle prediction tool which is based on the space-variant transition probability matrix obtained from an actual vehicle speed dataset. Then, a vehicle and an engine model is developed to predict the engine performance depending on the calibration for the estimated driving cycle. Finally, a controller is proposed which adapts the start-of-injection calibration map to fulfil the [Formula: see text] emission constraint while minimising the fuel consumption. The calibration is adapted during a predefined time window based on the predicted engine performance on the estimated cycle and the difference between the actual and the constraint on engine [Formula: see text] emissions. The method assessment was done experimentally in the engine test set-up. The engine performace using the method is compared with the state-of-the-art static calibration method for different [Formula: see text] emission limits on real driving cycles. The online implementation of the method shows that the fuel consumption can be reduced by 3%–4% while staying within the emission limits, indicating that the estimation method is able to capture the main driving cycle characterstics.

Mechanism of neural network training for forecasting the meteorological situation when using GIS

2021 ◽  
pp. 22-29
Author(s):  
M.R. Vagizov ◽  
◽  
E.P. Istomin ◽  
O.N. Kolbina ◽  
A.S. Kochnev ◽  
...  
Keyword(s):  
Neural Network ◽  
Estimation Method ◽  
Stochastic Method ◽  
Neural Network Training ◽  
Forecast Method ◽  
Network Training ◽  
Meteorological Situation ◽  
Previous Sample ◽  
Data Processor ◽  
Using Data

This article is devoted to the mechanisms of neural network training for forecasting the meteorological situation when using GIS. The structural scheme of the GIS under consideration is proposed as a project solution and the main elements allowing to implement neural networks and their training are defined. The stochastic method is chosen as a tool for neural network training as it suggests the most probable outcome of the event based on the previous sample. The article gives an example of testing neural network training as an application program «Data Processor». The results described in the article allow us to judge about the applicability of the selected neural network training method for forecasting meteorological conditions and using data in geoinformation decision-making systems. Keywords: geoinformation system, synoptic forecast method, hydrodynamic forecast method, aggregator, data processor, knowledge base, deterministic method, expert estimation method, stochastic method, neural network, sampling, probability dispersion.

scholarly journals Vehicle Velocity Estimation Fusion with Kinematic Integral and Empirical Correction on Multi-Timescales

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1242
Author(s):  
Jiangyi Lv ◽  
Hongwen He ◽  
Wei Liu ◽  
Yong Chen ◽  
Fengchun Sun
Keyword(s):  
Autonomous Vehicles ◽  
Estimation Error ◽  
Longitudinal Velocity ◽  
Estimation Method ◽  
Velocity Estimation ◽  
Model Parameters ◽  
Lateral Velocity ◽  
Empirical Correction ◽  
Vehicle Velocity ◽  
Wide Range

Accurate and reliable vehicle velocity estimation is greatly motivated by the increasing demands of high-precision motion control for autonomous vehicles and the decreasing cost of the required multi-axis IMU sensors. A practical estimation method for the longitudinal and lateral velocities of electric vehicles is proposed. Two reliable driving empirical judgements about the velocities are extracted from the signals of the ordinary onboard vehicle sensors, which correct the integral errors of the corresponding kinematic equations on a long timescale. Meanwhile, the additive biases of the measured accelerations are estimated recursively by comparing the integral of the measured accelerations with the difference of the estimated velocities between the adjacent strong empirical correction instants, which further compensates the kinematic integral error on short timescale. The algorithm is verified by both the CarSim-Simulink co-simulation and the controller-in-the-loop test under the CarMaker-RoadBox environment. The results show that the velocities can be accurately and reliably estimated under a wide range of driving conditions without prior knowledge of the tire-model and other unavailable signals or frequently changeable model parameters. The relative estimation error of the longitudinal velocity and the absolute estimation error of the lateral velocity are kept within 2% and 0.5 km/h, respectively.

Steering Strategy for a Multi-Axle Wheeled Vehicles

2018 ◽  
Author(s):  
Waqar Ahmed ◽  
Raja Amer Azim ◽  
Sana Fatima
Keyword(s):  
Mathematical Model ◽  
Single Unit ◽  
Steering System ◽  
Vehicle Speed ◽  
Wheel Slip ◽  
Turn Radius ◽  
Heavy Loads ◽  
The Mathematical Model ◽  
Wheeled Vehicles ◽  
Good Vehicle

This paper presents a mathematical model for multi-axle steering vehicles operating on level ground. For transporting heavy loads vehicles with multiple axles are required. Apart from added complexity steering of multiple axle for turning is a big challenge. Due to type of load being carried a single unit vehicle is sometimes preferred. The mathematical model of a six axle vehicle with 4-axle steering system is developed. Simulations at various track radii, vehicle speeds and steering ratios (ratio between the first, second, fifth and sixth steering axle) are performed. Axle steering angles and wheel slip angles are evaluated. The steering ratio requirements vary with vehicle speed and turn radius. A configuration is selected for better performance for a wider range. The resulting steering ratios show good vehicle maneuverability, stability and steering efficiency.

scholarly journals An Analysis of the Systematic Error of a Remote Method for a Wattmeter Adjustment Gain Estimation in Smart Grids

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 37 ◽  
Author(s):  
Robertas Lukočius ◽  
Žilvinas Nakutis ◽  
Vytautas Daunoras ◽  
Ramūnas Deltuva ◽  
Pranas Kuzas ◽  
...  
Keyword(s):  
Systematic Error ◽  
Power Factor ◽  
Smart Grids ◽  
Low Voltage ◽  
Voltage Drop ◽  
Estimation Method ◽  
Data Communication ◽  
Pattern Search ◽  
Error Monitoring ◽  
Worst Case

Smart energy meters supporting bidirectional data communication enable novel remote error monitoring applications. This research targets characterization of the systematic worst-case error of the previously published remote watthour meter’s gain estimation method based on the comparison of synchronous measurements by the reference and meter under test. To achieve the research aim a methodology based on global maximization of the systematic error objective function assuming the typical low voltage electrical distribution network operation parameters ranges as defined by the standard recommendations for network design. To cross verify the reliability of the assessed solutions the suggested error analysis methodology was implemented utilizing two stochastic global extremum search techniques (genetic algorithms, pattern search) and the third one utilizing nonlinear programming solver. It was determined that the wattmeter adjustment gain worst-case error does not exceed 0.5% if the remote wattmeter monitored load power factor is larger than 0.1 and a network is designed according to the recommendation of the acceptable voltage drop less than 5%. For a load exhibiting power factor larger than cos φ = 0.9 the worst-case error was found to be less than 0.1%. It is concluded therefore that considering the systematic worst-case error the previously suggested remote wattmeter adjustment gain estimation method is suitable for remote error monitoring of Class 2 and Class 1 wattmeters.

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