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The electric golf cart of LIPI is designed traditionally without calculating geometric and kinematic properties of it steering layout. Furthermore, it resulting less quality of handling and make it less safe to operate. The kinematics calculation of steering linkages has been explained by Ackerman. So, this paper's purpose is to calculate and make...
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This paper studies and compares the gap selection process of multiple vehicle classes (passenger cars, delivery vans, and trucks) within their discretionary lane changing activities. Given a trajectory or a sequence of gap selection decisions, we aim to predict whether a vehicle will change or keep a lane. For this purpose, we use a large trajector...
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... Electric golf carts [1] serve diverse roles in various environments. They are commonly used in shopping malls to assist elderly patrons in navigating long distances. ...
... Consequently, during motor standstill, it draws maximum current. The transfer function of a DC brush motor, articulated by R. Barua and colleagues [54] and denoted by (1), establishes the correlation between input voltage ( ) and output angular rotation rate (). The parameters employed in the equations of this system, gleaned from the research [54], are outlined in Table 1 and (2) to furnish data for the development of the control system in this investigation. ...
This study investigates methods to improve steering control for electric ambulance golf carts by conducting a comparative analysis of fuzzy logic controllers. The research assesses four control systems, PD controller, fuzzy PD controller, fuzzy PD+I controller, and PBC and PD+I type fuzzy logic controller – to determine their effectiveness in enhancing steering control. Simulink simulations are employed to evaluate the performance of these controllers under various conditions. Results indicate that the PBC and PD+I type fuzzy logic controller demonstrates superior performance, showing significant reductions in both rise time and settling time with minimal overshoot compared to other controllers. The findings underscore the potential of fuzzy logic controllers in enhancing steering control for electric vehicles. Future research should explore alternative control strategies and assess controller robustness under diverse operating conditions.
... The control system is shown in Figure 6. Wheel angle in vehicles is known to be in the range of [-30 o , + 30 o ] [14]. The electric vehicle prototype was tested on three road conditions with different friction coefficients and circular road trajectory with 5 o , 15 o and 25 o steering angles and the results were observed. ...
... (7), the mathematical expression of the slip in wheel speed for vehicles is given. This expression is one of the most important parameters that express whether the speed of vehicle catches to the reference speed or not [14]. In line with the tests performed with the EDS control, the average slip value was calculated for three different test aeras and three different steering angles by using eq.(7). ...
... Approximate friction coefficients of test areas[14] ...
The harmful gases emitted by vehicles using oil-based fuels have been widely discussed in recent years. For this reason, in vehicle technology, a tendency has started to use vehicles with lower greenhouse gas effect engine types. Electric motor vehicles are more complex in terms of control when compared to internal combustion engine vehicles. However, it offers a much more comfortable use for essential needs such as cleaning, maintenance and repair. There are many studies in the literature on mathematical simulations of electronic differential system (EDS) and laboratory scale EDS trials for electric vehicles. In this study, the mathematical model of EDS for an electric vehicle, is simulated. Unlike previous studies, the mathematical model of EDS was embedded on a microprocessor and used to control a prototype electric vehicle. Real road tests were carried out with the prototype electric vehicle. Simulation and road tests were carried out under 3 different road conditions (dry, wet and slippery) and 3 different steering angles (5^o, 〖15〗^o, ve 〖25〗^o). In order to interpret the results, current and speed data of the right and left wheels on the prototype vehicle were taken in real time. The results confirm that the vehicle does not spin when turning in different road conditions.
... It improves the steering accuracy and simplifies operation. To ensure steering operation safety, frequency conversion speed regulation technology was combined with a full hydraulic redirector system [20,21] to develop and improve a frequency conversion hydraulic redirector [22][23][24]. Appropriate structures and control strategies have been designed to overcome the nonlinear factors that affect the power performance of redirectors. Furthermore, a more effective use of the redirector energy was realized, and the robustness of the system was improved [25][26][27]. ...
Load-sensing steering systems for articulated loaders are prone to large pressure shocks and oscillations during steering operations, affecting the system stability. An optimized structure of the redirector with bypass damping is proposed to improve this phenomenon. In this structure, orifices and throttle grooves are added to the traditional redirector. To control the steering load and working conditions, the steering load of the loader is replaced by a pressure regulating valve. Simulation and experimental results reveal that the redirector with bypass damping has better load-sensing characteristics than the traditional redirector. The peak output pressure shock caused by the load unit step signal decreases from 6.50 to 5.64 MPa, which means the pressure oscillation of the hydraulic system is reduced by 13.4%. The pressure fluctuation time can be reduced from 2.09 to 1.6 s, with a decrease rate of 23.4%. The output pressure oscillation decays swiftly, and the smoothness of the steering operation is improved significantly.
... • Development and testing of PD/PI fuzzy logic controller [5] • Design of an autonomous mobile robot [6] • Fuel management with a hybrid system [7] • Braking problems for golf carts and other low-speed vehicles [8] • Development of the battery and charging system of the golf cart [9] • Braking stability on personal transport, golf and lowspeed vehicles [10] • Development of the fuel cell control system [11] • A fuzzy knowledge-based algorithm for the estimation of the traction force [12] • -Preventing backward throwing problems during manoeuvring with rapid acceleration [1] • Effects of hybrid fuel cells on driving performance [13] • Evaluation of the electrical power requirements, energy recovery and environmental pollution [14] • Design of an autonomous golf cart considering the effects of environmental, human and scaling factors in system design [15] • Calculation of kinematic properties on the angle of rotation and steering axis [16] • Performance analysis on a solar-powered golf cart [4] • -Design and experimental tests of the solar charger for a solar-powered electric golf cart [17] • Re-using of the second life batteries for the electric golf carts [18] • Development adaptive Monte Carlo localizations algorithm for autonomous golf cart [19] As seen in summarized golf cart studies, a specific study has not been found regarding the improvement of the traction motor. ...
This paper proposes the traction motor analysis and weight reduction for an electric golf car with 1 + 5 passengers, because the power to weight ratio is the critical parameter for the electric vehicle in terms of the vehicle performance. Firstly, the induction motor (IM) already used in the electric golf car is tear-downed and modelled in a simulation environment, and the model is verified by the test results given in the datasheet to prove the accuracy of the model used in the design. Secondly, the vehicle dynamics of the electric golf car are investigated and the traction requirements are determined in the simulation environment. The design parameters of the IM model are investigated by using Taguchi’s design of experiment (DoE) method, and the critical design parameters are specified. Then, a neural network (NN) to predict better design parameters is trained to operate with the DoE model according to the prioritization of framework. Finally, the study is completed by comparing the obtained results of the NN-predicted IM model, DoE best-case IM model and the original IM model in terms of the battery consumption, power to weight ratio, efficiency and vehicle traction requirements.
... Saurabh et al.)[47] Design of Suspension System for Formula Student Race Car using SolidWorks software and the Finite element analysis of the components are done using ANSYS Workbench. The static analysis yields the required stiffness of spring along with the sustainability of components from FE analysis. ...
Electric vehicle drives offer several advantages over conventional internal combustion engines,
especially in terms of lower local emissions, higher energy efficiency, and decreased dependency upon
oil. The objective of this Dissertation is to design, build, and test an electric car. Therefore, to design
the electric car, a full-car simulation is required to select the best components, using MATLAB
software. In this Dissertation, a full-car vehicle dynamics model developed in the Simulink
environment. The model uses real scenario driving cycle and wheels inputs and provides outputs
similar to the sensors mounted on the actual vehicle. The selection of components based on the
mathematical model real-time simulation by applying multi-combination scenarios to investigate the
most appropriate size for each mechanical and electrical element to reach the vehicle requirements. A
very important part of this Dissertation concernsthe model validation of a micro wind turbine installing
in the top front of the vehicle near to the stagnation points where the presser and form drag have the
highest values. The blade element theory used to illustrate the behaviour and characteristic of the
turbine's blades to investigate the most accurate analytical efficiency. By using, the iterative solution
method implemented with MATLAB program
... To be applied to the vehicle steering subsystem, the high-level control action (α) is converted to robot's steering angle (δ) using Eq. 2. Subsequently, the steering angle must be transformed to a numerical command in accordance with a steering polynomial that was extracted following the methodology presented by Khristamto et al. (2015). Additionally, the high-level control system block also sends a second signal to the low-level control system. ...
... Since the development of a control system based on the H∞ optimization technique demands the use of a well-defined mathematical model (Khristamto et al. 2015), the vehicle modeling procedure was carried out as a first step. Figure 4a presents a kinematic representation for a car-like vehicle based on the previous work of Aström and Murray (2010). ...
... The use of this proposed kinematic model demands the following assumptions: (a) the vehicle has a planar motion; (b) slip angles at both wheels are null. According to Jazar (2013), Rajamani (2006) and Khristamto et al. (2015), such assumptions are reasonable for low-speed vehicle motion (lower than 5 m/s) as the lateral forces generated by the tires are small at low speeds; (c) The wheels roll without slip. Another fundamental assumption for the kinematic model definition is that the vehicle wheelbase ( L ) is much smaller than the magnitude of the curvature radius that the vehicle may perform (Khristamto et al. 2015; Aström and Murray 2010). ...
Severe working conditions, the cost reduction need and production growth justify the adoption of technological techniques in agricultural production. Currently, Global Navigation Satellite System (GNSS) based navigation systems are very popular in agriculture. However, relying only on GNSS data and the availability of crop maps that also need to be updated may become a problem. One may face lack of GNSS satellite signal during the path and the navigation system may fail. As an alternative, this paper presents the modeling, development and validation of a reactive navigation system for agricultural fields based on a frontal light detection and ranging (LiDAR) sensor and a H∞ robust controller. A small-scale mobile robot (Helvis3) was used to validate the controllers and carry out experiments in both controlled and farm scenarios. According to the experimental results, the proposed navigation system is capable of controlling the robot displacement between crop rows, keeping it in the middle of the corresponding path with minimum error, despite environmental disturbances.
... For these purposes a 2D space was created. In the first attempt, with no IMU sensor attached, a single XY plane is represented and limited by the Ackermann configuration [5]. As stated before, a map is a mandatory requirement in order to establish the best route. ...
The project approach in teaching is now considered a promising method that relates the learning process to the conditions of solving real problems. Student interest stimulates in the topic under study, giving them differentiated skills, including those that are related to teamwork. This also allows students with different interests and levels of preparation to work simultaneously on the solution of one problem. Application of the project approach for training in complex new areas requires trained equipment and specialists. The specialists direct the process of creative search for students in gaining relevant knowledge, as well as specifics in determining the problem under study.
... Then, space requirement ∆ = − . More specifically can be described as follows: Figure 2. Calculate space requirement [11] Turning radius calculation with the Ackermann cannot be done when the vehicle is on the move at high speeds, so the testing is done at low speed. Problems can also occur because the two front wheels are fitted independent motors. ...
The development of alternative vehicle were continued by designing hybrid vehicle that using compressed air and electrical propulsion. This compressed air propulsion on the rear wheels and two electric motor as a front wheel drive (FWD) were installed independently, where left and right can rotate with different speeds and direction. Independent FWD could be a problem when two wheels has a different rotation. The first experiment was tested by measuring the rotation per minute (RPM) on each wheel. Measurement were performed by varying the position of the throttle pedal. The result of measurements on both wheels rotating speed showed a difference of 1 %. The second test was to compare the space requirement, which derived from the function of cornering radius. Space requirement for inactive vehicle cornering system is 4.52 meters and 3.39 meters when system is active.
... The path planning problem is a well-known NP-hardness [3] where the complexity increases with the degrees of freedom of the vehicle. In this work, the ground vehicle is reduced to a 2D space of a single plane -where the component is neglected and the vehicle is restricted by some constraints due to the Ackermann configuration [4]. The aim of solving this NP-hardness is not to find one solution that connects the start point and the goal point, but the optimal solution with the minimum distance and the smoothest maneuvers and without hitting any known obstacles. ...
The aim of this work is to integrate and analyze the performance of a path planning method based on Time Elastic Bands (TEB) in real research platform based on Ackermann model. Moreover, it will be proved that all modules related to the navigation can coexist and work together to achieve the goal point without any collision. The study is done by analyzing the trajectory generated from global and local planners. The software prototyping tool is Robot Operating System (ROS) from Open Source Robotics Foundation and the research platform is the iCab (Intelligent Campus Automobile) from University Carlos III. This work has been validated from a test inside the campus where the iCab has performed the navigation between the starting point and the goal point without any collision. During the experiment, we proved the low sensitivity of the TEB method to variations of the vehicle model configuration and constraints.
Human error is the most significant factor in traffic accidents. 61% of accidents in Indonesia are caused by driver negligence. Autonomous vehicles are unmanned vehicles that are believed to be able to reduce the number of accidents caused by human error. This study aims to create a prototype of a small-scale unmanned vehicle using computer vision that can move around the track. The prototype captures an image using a USB webcam and is processed by a Raspberry Pi 4 to predict the correct steering angle based on input from the camera. A convolutional neural network (CNN) algorithm is used to recognize the path. The material used to make the prototype is PLA (polylactic acid). The prototype steering system uses a servo motor, and the drive system uses a brushless DC motor controlled by the PCA9685 module. More than 1600 image data were used and taken based on a simplified track. The results of this study indicate that the prototype can move along the given track with a steering angle range of 20°–130° for right turns and 60°–170° for left turns. The throttle value capable of moving the prototype at a steady speed is 0.075. The Keras Tensorflow model, dataset, and autonomous car design can achieve the desired level of autonomy with an RMSE accuracy of 0.1145.
