A High Fuel Consumption Efficiency Management Scheme for PHEVs Using an Adaptive Genetic Algorithm

Lee, Wah Ching; Tsang, Kim Fung; Hao, Ran; Hung, Faan Hei; Wu, Chung Kit; Chui, Kwok Tai; Lau, Wing Hong; Leung, Yat Wah

doi:10.3390/s150101245

Cited by 13 publications

(4 citation statements)

References 14 publications

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“…When real time control command is considered, a fast and simple-programming algorithm like GA should be adopted as the backbone algorithm for the control system. Fusion of FL and GA can combine their strength as well as reduce their limitations [20].…”

Section: Background Of Methodologymentioning

confidence: 99%

An Adaptive Indoor Air Quality Control Scheme for Minimizing Volatile Organic Compounds Density

Hung

Tsang

et al. 2020

IEEE Access

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Volatile organic compounds (VOCs) such as toluene, xylene, and formaldehyde are commonly found in indoor and the VOCs will yield human health's issue. The compounds are crucial in determining the indoor air quality (IAQ) and hence being how to manage IAQ becomes an important topic. Most human may spend most of time living in poor IAQ environment and it may result in excess life risk to respiratory symptoms and billion US dollars cost annually. VOC degrades IAQ and high VOC density indoor is not uncommon. The World Health Organization (WHO) and the Government of Canada provided benchmarks on the harm levels and the benchmarks indicated the potential health risk caused by hazardous substances. In this paper, a new comprehensive control scheme, namely fuzzy genetic multi-layer control scheme (FGMLCS), is designed to manage the IAQ. The multilayer control structure is designed which includes fuzzy logic together with genetic algorithm and multi-objective optimization to give an optimal control for a better IAQ. Q factor is defined based on the ''harm levels'' set by the benchmarks to give a unified standard for various VOCs with different ''harm levels''. FGMLCS has achieved VOC density better than the ''harm levels'' by over 57%, which is superior to the benchmarks and is able to lower the risk of health deterioration and thus aiding habitant to be less carcinogenic.

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Section: Background Of Methodologymentioning

confidence: 99%

An Adaptive Indoor Air Quality Control Scheme for Minimizing Volatile Organic Compounds Density

Hung

Tsang

et al. 2020

IEEE Access

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“…Then the data analysis server can analyse the movement information and the fuel quantity information to estimate the fuel consumption based on driver behaviours without fuel sensors for saving costs. The proposed fuel consumption estimation method is designed based on a GA [17][18][19] which can generate gene sequences and use crossover and mutation to retrieve an adaptable gene sequence. The adaptable gene sequence can be applied as the set of fuel consumption in accordance with the pattern of driver behaviour.…”

Section: Fuel Consumption Estimation Systemmentioning

confidence: 99%

Fuel Consumption Estimation System and Method with Lower Cost

Chen

Kuan

et al. 2017

Symmetry

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This study proposes a fuel consumption estimation system and method with lower cost. On-board units can report vehicle speed, and user devices can send fuel information to a data analysis server. Then the data analysis server can use the proposed fuel consumption estimation method to estimate the fuel consumption based on driver behaviours without fuel sensors for cost savings. The proposed fuel consumption estimation method is designed based on a genetic algorithm which can generate gene sequences and use crossover and mutation for retrieving an adaptable gene sequence. The adaptable gene sequence can be applied as the set of fuel consumption in accordance with the pattern of driver behaviour. The practical experimental results indicated that the accuracy of the proposed fuel consumption estimation method was about 95.87%.

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“…The traveling salesman problem (TSP) is a typical non-deterministic polynomial (NP)hard problem with the goal of designing the shortest route for a traveler to visit each city without repetition, followed by returning to the starting city. In production and life, TSP has been widely used as a model in many fields, such as vehicle path planning [1,2,3], machine learning [4], temporal graphs [5], word sense disambiguation [6], green logistics [7], fuel efficiency management [8], wireless charging [9], and so on. Hence, solving the TSP is of great significance for household, civil, and military applications.…”

Section: Introductionmentioning

confidence: 99%

An Improved Genetic Algorithm for Path-Planning of Unmanned Surface Vehicle

Xin

Zhong

Yang

et al. 2019

Sensors

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The genetic algorithm (GA) is an effective method to solve the path-planning problem and help realize the autonomous navigation for and control of unmanned surface vehicles. In order to overcome the inherent shortcomings of conventional GA such as population premature and slow convergence speed, this paper proposes the strategy of increasing the number of offsprings by using the multi-domain inversion. Meanwhile, a second fitness evaluation was conducted to eliminate undesirable offsprings and reserve the most advantageous individuals. The improvement could help enhance the capability of local search effectively and increase the probability of generating excellent individuals. Monte-Carlo simulations for five examples from the library for the travelling salesman problem were first conducted to assess the effectiveness of algorithms. Furthermore, the improved algorithms were applied to the navigation, guidance, and control system of an unmanned surface vehicle in a real maritime environment. Comparative study reveals that the algorithm with multi-domain inversion is superior with a desirable balance between the path length and time-cost, and has a shorter optimal path, a faster convergence speed, and better robustness than the others.

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A High Fuel Consumption Efficiency Management Scheme for PHEVs Using an Adaptive Genetic Algorithm

Cited by 13 publications

References 14 publications

An Adaptive Indoor Air Quality Control Scheme for Minimizing Volatile Organic Compounds Density

An Adaptive Indoor Air Quality Control Scheme for Minimizing Volatile Organic Compounds Density

Fuel Consumption Estimation System and Method with Lower Cost

An Improved Genetic Algorithm for Path-Planning of Unmanned Surface Vehicle

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