A Novel Adaptive Operation Mode based on Fuzzy Logic Control of Electrical Vehicle

Kraa, O.; Becherif, Mohamed; Ayad, M. Y.; Saadi, R.; Bahri, M.; Aboubou, A.; Tégani, I.

doi:10.1016/j.egypro.2014.06.024

Cited by 15 publications

(5 citation statements)

References 11 publications

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“…This method has been implemented to many sectors namely medical [12], farming [13] and also for detecting object using a stereo camera [14]. Furthermore, the researchers also used fuzzy method for electric vehicle applications for instance in energy reduction of vehicle consumption [15], regenerative braking [16], autonomous controlling vehicle in roundabout [17], parking lot [18], improvement of visual detection for pedestrian crossing [19]. This paper utilizes fuzzy system built via MATLAB toolbox.…”

Section: Braking Decisionmentioning

confidence: 99%

Camera Based Artificial Intelligence for A Smart Vehicle Braking System

Prasetya

Ridlwan

Budiono³

et al. 2020

IJETER

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A braking system is an essential value in a vehicle particularly for a safety precaution. The higher number rate of traffic accidents mostly in Indonesia shows that the dominant cause of accidents is due to the human factor. The physical condition such as tired or sleepy during driving is the primary problem according to the survey. In order to assist a person when driving a vehicle, an artificial intelligence method is necessary to be integrated to ensure the safety of surrounding people inside and outside the vehicle. This study focuses on implementing the method of identifying object and distance to provide an indicator for braking action. Images from a stereo camera is processed by a neural network technique via a mini computer to classify as well as the distance of objects. Furthermore, selection of priorities are done to obtain the intensity of braking action. The result shows that process of classification and measurement requires period around 200 ms. Furthermore, braking action done by fuzzy controller sub-system shows that the intensity has smoother signal with the object distance variation compare to the direct method. Objects are firstly identified by the presence of a stereo camera, later on the decision of braking intensity is generated by two processing unit namely conventional and fuzzy unit. This is achieved by processing the data saved from the object detection using two system via MATLAB software. The object identification result, distance measurement and the period of object detection is presented. Moreover, the response of braking intensity using data is processed with both conventional and fuzzy unit systems are also presented. he implementation of this study is for the heavy vehicle such buses or trucks that requires higher safety during the journey.

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Section: Braking Decisionmentioning

confidence: 99%

Camera Based Artificial Intelligence for A Smart Vehicle Braking System

Prasetya

Ridlwan

Budiono³

et al. 2020

IJETER

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“…The SOC of the battery can be obtained according to current integration. 18 It is shown in the following formula…”

Section: Soc Calculation Module Of Batterymentioning

confidence: 99%

A study of novel regenerative braking system based on supercapacitor for electric vehicle driven by in-wheel motors

Jin

Zheng

et al. 2015

Advances in Mechanical Engineering

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Taking supercapacitor and battery pack as the energy storage unit, a novel type of regenerative braking system for electric vehicle driven by in-wheel motors is presented, and a braking energy regeneration control strategy is set up. Then, a co-simulation test based on CRUISE and Simulink is conducted. The results of simulation show that the novel type of system can ensure the safety of battery pack and significantly improve the rate of energy regeneration.

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“…Given that fuzzy logic control is simple, can be easily realized, doesn't require modeling and has strong robustness, it is more appropriate to use in applications where parameters and/or model are undefined or changeable [9]. Fuzzy logic controllers (FLC) were; therefore, used in many applications to manage the energy in HRES.…”

Section: Type-1 Fuzzy Logic Conceptsmentioning

confidence: 99%

A type-1 fuzzy logic algorithm to manage the flow of energy in a stand-alone PV/wind/battery hybrid system

Faquir

Yahyaouy

Tairi

et al. 2015

2015 Intelligent Systems and Computer Vision (ISCV)

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The significant increase in the prices of conventional energy sources and the public awareness of the need to reduce global warming have encouraged many countries to develop new systems based on renewable energies. Combining renewable energy sources with storage units to form a multi source system can provide a more economic, and reliable supply of electricity in all load demand conditions compared to a singleuse of such systems. The energy balance between production and consumption should be carefully conducted while choosing the storage method to ensure the availability of power on demand and improve the dynamic behavior of the hybrid system. This paper presents a study of a HRES composed of Photovoltaic (PV) solar panels and a wind turbine as primary energy sources and batteries as storage units and proposes a computer algorithm based on type-1 fuzzy logic to control the energy between production and consumption and ensure the availability of power on demand.Keywords-Hybrid Renewable energy system, computer algorithm, energy management, wind turbine, Photovoltaic panels, type-1 fuzzy logic.

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A Novel Adaptive Operation Mode based on Fuzzy Logic Control of Electrical Vehicle

Cited by 15 publications

References 11 publications

Camera Based Artificial Intelligence for A Smart Vehicle Braking System

Camera Based Artificial Intelligence for A Smart Vehicle Braking System

A study of novel regenerative braking system based on supercapacitor for electric vehicle driven by in-wheel motors

A type-1 fuzzy logic algorithm to manage the flow of energy in a stand-alone PV/wind/battery hybrid system

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