The Experts below are selected from a list of 4278 Experts worldwide ranked by ideXlab platform
Tanguy Bouton - One of the best experts on this subject based on the ideXlab platform.
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Optimal charging strategy to minimize electricity cost and prolong battery life of electric Bus Fleet
2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Smart charging is becoming an important and indispensable asset for electric Bus Fleet to become economically competitive. This paper proposes an innovative approach for setting overnight charging schedules of electric Bus Fleet. This approach uses nonlinear programming in order to minimize both the electricity cost and the battery aging. The optimization is constrained by the operating Buses conditions, the electric vehicle supply equipment, and the power grid. A comparison between the nonlinear programming results and non-dominated sorted genetic algorithm (NSGA-II) will show the difference and complementarities of both approaches and proposes a number of trade-off optimal solutions. Keywords-multi-objective optimization problem (MOP), battery aging, electric vehicles (EVs), electric Buses (EBs), Pareto front, non-dominated sorted genetic algorithm (NSGA), nonlinear programming (NLP), two phase method (TPM), Fleet operator (FO)
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Optimal Scheduling to Manage an Electric Bus Fleet Overnight Charging
Energies, 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Electro-mobility is increasing significantly in the urban public transport and continues to face important challenges. Electric Bus Fleets require high performance and extended longevity of lithium-ion battery at highly variable temperature and in different operating conditions. On the other hand, Bus operators are more concerned about reducing operation and maintenance costs, which affects the battery aging cost and represents a significant economic parameter for the deployment of electric Bus Fleets. This paper introduces a methodological approach to manage overnight charging of an electric Bus Fleet. This approach identifies an optimal charging strategy that minimizes the battery aging cost (the cost of replacing the battery spread over the battery lifetime). The optimization constraints are related to the Bus operating conditions, the electric vehicle supply equipment, and the power grid. The optimization evaluates the fitness function through the coupled modeling of electro-thermal and aging properties of lithium-ion batteries. Simulation results indicate a significant reduction in the battery capacity loss over 10 years of operation for the optimal charging strategy compared to three typical charging strategies.
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Optimal Charging Strategy to Minimize Electricity Cost and Prolong Battery Life of Electric Bus Fleet
2019 IEEE Vehicle Power and Propulsion Conference (VPPC), 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Smart charging is becoming an important and indispensable asset for electric Bus Fleet to become economically competitive. This paper proposes an innovative approach for setting overnight charging schedules of electric Bus Fleet. This approach uses nonlinear programming in order to minimize both the electricity cost and the battery aging. The optimization is constrained by the operating Buses conditions, the electric vehicle supply equipment, and the power grid. A comparison between the nonlinear programming results and non-dominated sorted genetic algorithm (NSGA-II) will show the difference and complementarities of both approaches and proposes a number of trade-off optimal solutions.
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A quadratic programming based optimisation to manage electric Bus Fleet charging
International Journal of Electric and Hybrid Vehicles, 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:The use of electric Buses (EBs) is expected to increase significantly in the coming years. Uncontrolled charging of EBs can affect not only the power grid (grid instability, harmonic pollution...) but also the operating cost. This paper introduces an optimal charging strategy based on charging schedule planning and modulation of charging power for a Fleet of electrically powered Buses. The optimal charging strategy allows minimising the charging cost as well as the load power variations using quadratic programming. The proposed quadratic programming can significantly reduce the computation time and simultaneously handle a large Bus Fleet. First results indicate a significant reduction in customer energy bills while avoiding potential penalties due to peak loads.
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Multi-Objective Optimisation of the Management of Electric Bus Fleet Charging
2017 IEEE Vehicle Power and Propulsion Conference (VPPC), 2017Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Tanguy Bouton, Eduardo Redondo-iglesiasAbstract:The paper introduces a methodical approach, which can be used to identify a charging strategy for a Fleet of electrical Buses in urban Bus services. This method uses evolutionary algorithms with multi-objective optimisation in order to reduce electricity costs and battery ageing taking into account technical constraints (e.g. peak load demand, charging technology). In this work, we present an application of this global method illustrated with a case study of one specific Bus operating on an existing Bus line. An optimal charging strategy is identified while optimising both electricity costs and battery ageing. First results show that the optimal charging strategy achieves improvements in reducing costs as well as enhancing the battery lifetime.
Feng Xiao - One of the best experts on this subject based on the ideXlab platform.
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mixed Bus Fleet location routing scheduling under range uncertainty
Transportation Research Part B-methodological, 2021Co-Authors: Wei Huang, Feng XiaoAbstract:Abstract This paper develops a framework to address the multi-depot vehicle location-routing-scheduling problem with multi-vehicle types, including electric Buses, under range uncertainty. Three major issues in Bus routing and scheduling are addressed in this framework, i.e., uncertain driving range, refueling or charging need, and locating refueling or charging facilities. Mathematically, the problem is formulated as a two-stage stochastic program. Two types of services, regular services running on fixed schedules and ad hoc services to cover incomplete scheduled trips arising from energy shortage of certain Buses, are considered in this paper. An adaptive time-space-energy network is developed to model the refueling issues and location problem. We introduce the notion of range reliability to decompose and solve the two-stage stochastic formulation under range uncertainty. The regular services schedule is determined in stage-one to cover the demand under a certain range reliability level. Upon realization of the random driving range, the deployment of ad hoc services is made in stage-two to address the occurrence of energy shortage of certain Buses. A range reliability-based gradient algorithm is developed to minimize the expected total cost of the system. We then apply the proposed method to Bus services in Hong Kong. The range reliability-based approach shows promising results, leading to substantial cost savings as compared with the traditional methods that ignore the effects of driving range uncertainty.
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mixed Bus Fleet scheduling under range and refueling constraints
Transportation Research Part C-emerging Technologies, 2019Co-Authors: Feng XiaoAbstract:Abstract This paper develops a formulation for the multiple depot (MD) vehicle scheduling problem with multiple vehicle types (MVT), including electric Buses (EBs), under range and refueling constraints. A novel approach is developed to generate the feasible time-space-energy (TSE) network for Bus flow and time-space (TS) network for passenger flow, where the range and refueling issues can be precisely addressed. We then introduce the external cost associated with emissions, and investigate the minimum total system cost to operators and passengers by scheduling the Bus Fleet and locating the refueling stations. The problem is formulated as an integer linear program (ILP) to find the global optimal solution. For computational efficiency, we develop a simplified formulation based on the TS Bus flow network to handle larger-scale problems for approximate solutions. We apply the methods to Bus services in Hong Kong to analyze the Bus Fleet size needed, operational cost, passenger cost, and emissions generated by Buses with multiple energy sources. Through the formulation, we study the implications of government subsidy for EBs, Bus scheduling in Low Emission Zone (LEZ), and safe driving ratio design for Bus refueling.
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mixed Bus Fleet management strategy for minimizing overall and emissions external costs
Transportation Research Part D-transport and Environment, 2016Co-Authors: Feng Xiao, Xuekai CenAbstract:Abstract Diesel Buses add substantially to air pollution. To mitigate this problem, more and more clean-energy Buses are introduced. Among them, electric Bus has been recognized as the cleanest with lower emissions. But the deployment of electric Bus is limited by its short travel distance and long charging time. In this paper, based on the approach of remaining life additional benefit-cost (RLABC), we propose an approach called new life additional benefit-cost (NLABC) to solve the mixed Bus Fleet management (MBFM) problem. An integer program is developed based on the NLABC analysis for maximizing the total net benefit of early replacement, where both the optimal Fleet size and composition under budget constraints can be determined. Arguably, the routing problem is a major issue to be tackled due to the range limitations and operating costs of electric Buses in the MBFM problem. Hence, we include the routing problem associated with Bus services coordination among multiple routes in this formulation. Two routing methods are proposed to solve the recharging problem to study the tradeoff between accuracy and efficiency. Four types of Buses, including electric Bus, compressed natural gas Bus, hybrid-diesel Bus, and diesel Bus, are considered, while accounting for their different operating costs, external costs of emissions, and purchase costs. To illustrate the approach, we apply the formulation to some transit lines in Hong Kong. The results show that vehicle routing with Bus service coordination and mixed Fleet optimization are important considerations for managing the Bus Fleet; both of which can produce considerable benefits.
Adnane Houbbadi - One of the best experts on this subject based on the ideXlab platform.
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Optimal charging strategy to minimize electricity cost and prolong battery life of electric Bus Fleet
2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Smart charging is becoming an important and indispensable asset for electric Bus Fleet to become economically competitive. This paper proposes an innovative approach for setting overnight charging schedules of electric Bus Fleet. This approach uses nonlinear programming in order to minimize both the electricity cost and the battery aging. The optimization is constrained by the operating Buses conditions, the electric vehicle supply equipment, and the power grid. A comparison between the nonlinear programming results and non-dominated sorted genetic algorithm (NSGA-II) will show the difference and complementarities of both approaches and proposes a number of trade-off optimal solutions. Keywords-multi-objective optimization problem (MOP), battery aging, electric vehicles (EVs), electric Buses (EBs), Pareto front, non-dominated sorted genetic algorithm (NSGA), nonlinear programming (NLP), two phase method (TPM), Fleet operator (FO)
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Optimal Scheduling to Manage an Electric Bus Fleet Overnight Charging
Energies, 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Electro-mobility is increasing significantly in the urban public transport and continues to face important challenges. Electric Bus Fleets require high performance and extended longevity of lithium-ion battery at highly variable temperature and in different operating conditions. On the other hand, Bus operators are more concerned about reducing operation and maintenance costs, which affects the battery aging cost and represents a significant economic parameter for the deployment of electric Bus Fleets. This paper introduces a methodological approach to manage overnight charging of an electric Bus Fleet. This approach identifies an optimal charging strategy that minimizes the battery aging cost (the cost of replacing the battery spread over the battery lifetime). The optimization constraints are related to the Bus operating conditions, the electric vehicle supply equipment, and the power grid. The optimization evaluates the fitness function through the coupled modeling of electro-thermal and aging properties of lithium-ion batteries. Simulation results indicate a significant reduction in the battery capacity loss over 10 years of operation for the optimal charging strategy compared to three typical charging strategies.
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Optimal Charging Strategy to Minimize Electricity Cost and Prolong Battery Life of Electric Bus Fleet
2019 IEEE Vehicle Power and Propulsion Conference (VPPC), 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Smart charging is becoming an important and indispensable asset for electric Bus Fleet to become economically competitive. This paper proposes an innovative approach for setting overnight charging schedules of electric Bus Fleet. This approach uses nonlinear programming in order to minimize both the electricity cost and the battery aging. The optimization is constrained by the operating Buses conditions, the electric vehicle supply equipment, and the power grid. A comparison between the nonlinear programming results and non-dominated sorted genetic algorithm (NSGA-II) will show the difference and complementarities of both approaches and proposes a number of trade-off optimal solutions.
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A quadratic programming based optimisation to manage electric Bus Fleet charging
International Journal of Electric and Hybrid Vehicles, 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:The use of electric Buses (EBs) is expected to increase significantly in the coming years. Uncontrolled charging of EBs can affect not only the power grid (grid instability, harmonic pollution...) but also the operating cost. This paper introduces an optimal charging strategy based on charging schedule planning and modulation of charging power for a Fleet of electrically powered Buses. The optimal charging strategy allows minimising the charging cost as well as the load power variations using quadratic programming. The proposed quadratic programming can significantly reduce the computation time and simultaneously handle a large Bus Fleet. First results indicate a significant reduction in customer energy bills while avoiding potential penalties due to peak loads.
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Multi-Objective Optimisation of the Management of Electric Bus Fleet Charging
2017 IEEE Vehicle Power and Propulsion Conference (VPPC), 2017Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Tanguy Bouton, Eduardo Redondo-iglesiasAbstract:The paper introduces a methodical approach, which can be used to identify a charging strategy for a Fleet of electrical Buses in urban Bus services. This method uses evolutionary algorithms with multi-objective optimisation in order to reduce electricity costs and battery ageing taking into account technical constraints (e.g. peak load demand, charging technology). In this work, we present an application of this global method illustrated with a case study of one specific Bus operating on an existing Bus line. An optimal charging strategy is identified while optimising both electricity costs and battery ageing. First results show that the optimal charging strategy achieves improvements in reducing costs as well as enhancing the battery lifetime.
Eduardo Redondo-iglesias - One of the best experts on this subject based on the ideXlab platform.
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Optimal charging strategy to minimize electricity cost and prolong battery life of electric Bus Fleet
2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Smart charging is becoming an important and indispensable asset for electric Bus Fleet to become economically competitive. This paper proposes an innovative approach for setting overnight charging schedules of electric Bus Fleet. This approach uses nonlinear programming in order to minimize both the electricity cost and the battery aging. The optimization is constrained by the operating Buses conditions, the electric vehicle supply equipment, and the power grid. A comparison between the nonlinear programming results and non-dominated sorted genetic algorithm (NSGA-II) will show the difference and complementarities of both approaches and proposes a number of trade-off optimal solutions. Keywords-multi-objective optimization problem (MOP), battery aging, electric vehicles (EVs), electric Buses (EBs), Pareto front, non-dominated sorted genetic algorithm (NSGA), nonlinear programming (NLP), two phase method (TPM), Fleet operator (FO)
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Optimal Scheduling to Manage an Electric Bus Fleet Overnight Charging
Energies, 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Electro-mobility is increasing significantly in the urban public transport and continues to face important challenges. Electric Bus Fleets require high performance and extended longevity of lithium-ion battery at highly variable temperature and in different operating conditions. On the other hand, Bus operators are more concerned about reducing operation and maintenance costs, which affects the battery aging cost and represents a significant economic parameter for the deployment of electric Bus Fleets. This paper introduces a methodological approach to manage overnight charging of an electric Bus Fleet. This approach identifies an optimal charging strategy that minimizes the battery aging cost (the cost of replacing the battery spread over the battery lifetime). The optimization constraints are related to the Bus operating conditions, the electric vehicle supply equipment, and the power grid. The optimization evaluates the fitness function through the coupled modeling of electro-thermal and aging properties of lithium-ion batteries. Simulation results indicate a significant reduction in the battery capacity loss over 10 years of operation for the optimal charging strategy compared to three typical charging strategies.
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Optimal Charging Strategy to Minimize Electricity Cost and Prolong Battery Life of Electric Bus Fleet
2019 IEEE Vehicle Power and Propulsion Conference (VPPC), 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Smart charging is becoming an important and indispensable asset for electric Bus Fleet to become economically competitive. This paper proposes an innovative approach for setting overnight charging schedules of electric Bus Fleet. This approach uses nonlinear programming in order to minimize both the electricity cost and the battery aging. The optimization is constrained by the operating Buses conditions, the electric vehicle supply equipment, and the power grid. A comparison between the nonlinear programming results and non-dominated sorted genetic algorithm (NSGA-II) will show the difference and complementarities of both approaches and proposes a number of trade-off optimal solutions.
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A quadratic programming based optimisation to manage electric Bus Fleet charging
International Journal of Electric and Hybrid Vehicles, 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:The use of electric Buses (EBs) is expected to increase significantly in the coming years. Uncontrolled charging of EBs can affect not only the power grid (grid instability, harmonic pollution...) but also the operating cost. This paper introduces an optimal charging strategy based on charging schedule planning and modulation of charging power for a Fleet of electrically powered Buses. The optimal charging strategy allows minimising the charging cost as well as the load power variations using quadratic programming. The proposed quadratic programming can significantly reduce the computation time and simultaneously handle a large Bus Fleet. First results indicate a significant reduction in customer energy bills while avoiding potential penalties due to peak loads.
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Multi-Objective Optimisation of the Management of Electric Bus Fleet Charging
2017 IEEE Vehicle Power and Propulsion Conference (VPPC), 2017Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Tanguy Bouton, Eduardo Redondo-iglesiasAbstract:The paper introduces a methodical approach, which can be used to identify a charging strategy for a Fleet of electrical Buses in urban Bus services. This method uses evolutionary algorithms with multi-objective optimisation in order to reduce electricity costs and battery ageing taking into account technical constraints (e.g. peak load demand, charging technology). In this work, we present an application of this global method illustrated with a case study of one specific Bus operating on an existing Bus line. An optimal charging strategy is identified while optimising both electricity costs and battery ageing. First results show that the optimal charging strategy achieves improvements in reducing costs as well as enhancing the battery lifetime.
Serge Pelissier - One of the best experts on this subject based on the ideXlab platform.
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Optimal charging strategy to minimize electricity cost and prolong battery life of electric Bus Fleet
2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Smart charging is becoming an important and indispensable asset for electric Bus Fleet to become economically competitive. This paper proposes an innovative approach for setting overnight charging schedules of electric Bus Fleet. This approach uses nonlinear programming in order to minimize both the electricity cost and the battery aging. The optimization is constrained by the operating Buses conditions, the electric vehicle supply equipment, and the power grid. A comparison between the nonlinear programming results and non-dominated sorted genetic algorithm (NSGA-II) will show the difference and complementarities of both approaches and proposes a number of trade-off optimal solutions. Keywords-multi-objective optimization problem (MOP), battery aging, electric vehicles (EVs), electric Buses (EBs), Pareto front, non-dominated sorted genetic algorithm (NSGA), nonlinear programming (NLP), two phase method (TPM), Fleet operator (FO)
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Optimal Scheduling to Manage an Electric Bus Fleet Overnight Charging
Energies, 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Electro-mobility is increasing significantly in the urban public transport and continues to face important challenges. Electric Bus Fleets require high performance and extended longevity of lithium-ion battery at highly variable temperature and in different operating conditions. On the other hand, Bus operators are more concerned about reducing operation and maintenance costs, which affects the battery aging cost and represents a significant economic parameter for the deployment of electric Bus Fleets. This paper introduces a methodological approach to manage overnight charging of an electric Bus Fleet. This approach identifies an optimal charging strategy that minimizes the battery aging cost (the cost of replacing the battery spread over the battery lifetime). The optimization constraints are related to the Bus operating conditions, the electric vehicle supply equipment, and the power grid. The optimization evaluates the fitness function through the coupled modeling of electro-thermal and aging properties of lithium-ion batteries. Simulation results indicate a significant reduction in the battery capacity loss over 10 years of operation for the optimal charging strategy compared to three typical charging strategies.
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Optimal Charging Strategy to Minimize Electricity Cost and Prolong Battery Life of Electric Bus Fleet
2019 IEEE Vehicle Power and Propulsion Conference (VPPC), 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:Smart charging is becoming an important and indispensable asset for electric Bus Fleet to become economically competitive. This paper proposes an innovative approach for setting overnight charging schedules of electric Bus Fleet. This approach uses nonlinear programming in order to minimize both the electricity cost and the battery aging. The optimization is constrained by the operating Buses conditions, the electric vehicle supply equipment, and the power grid. A comparison between the nonlinear programming results and non-dominated sorted genetic algorithm (NSGA-II) will show the difference and complementarities of both approaches and proposes a number of trade-off optimal solutions.
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A quadratic programming based optimisation to manage electric Bus Fleet charging
International Journal of Electric and Hybrid Vehicles, 2019Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-iglesias, Tanguy BoutonAbstract:The use of electric Buses (EBs) is expected to increase significantly in the coming years. Uncontrolled charging of EBs can affect not only the power grid (grid instability, harmonic pollution...) but also the operating cost. This paper introduces an optimal charging strategy based on charging schedule planning and modulation of charging power for a Fleet of electrically powered Buses. The optimal charging strategy allows minimising the charging cost as well as the load power variations using quadratic programming. The proposed quadratic programming can significantly reduce the computation time and simultaneously handle a large Bus Fleet. First results indicate a significant reduction in customer energy bills while avoiding potential penalties due to peak loads.
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Multi-Objective Optimisation of the Management of Electric Bus Fleet Charging
2017 IEEE Vehicle Power and Propulsion Conference (VPPC), 2017Co-Authors: Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Tanguy Bouton, Eduardo Redondo-iglesiasAbstract:The paper introduces a methodical approach, which can be used to identify a charging strategy for a Fleet of electrical Buses in urban Bus services. This method uses evolutionary algorithms with multi-objective optimisation in order to reduce electricity costs and battery ageing taking into account technical constraints (e.g. peak load demand, charging technology). In this work, we present an application of this global method illustrated with a case study of one specific Bus operating on an existing Bus line. An optimal charging strategy is identified while optimising both electricity costs and battery ageing. First results show that the optimal charging strategy achieves improvements in reducing costs as well as enhancing the battery lifetime.
