Browsing by Subject "Energy management"

Now showing 1 - 9 of 9
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    Concurrent design of energy management and vehicle stability algorithms for a parallel hybrid vehicle using dynamic programming
    (AACC, 2012-06) Dokuyucu H. İbrahim; Çakmakçı, Melih
    In this paper, concurrent design of controllers for a vehicle equipped with a parallel hybrid powertrain is studied. Our work focuses on designing the two control algorithms, the energy management and the vehicle stability, concurrently which are traditionally considered separately. Dynamic Programming (DP) technique is used in order to obtain the optimal response trace for the controllers. In energy management strategy torque split ratio between engine and electric motor is used as a control signal. Additionally, in vehicle dynamics control strategy the torque split factor between front and rear axles is used as a control signal. Minimizing the fuel consumption and wheel slip is used as cost functions in energy management and vehicle dynamics control strategies respectively. Two dynamic problems are solved separately first and compared to the concurrent solution of the problems. Results show promising benefits can be obtained from the concurrent DP solution and rule extraction for designing better hybrid vehicle controllers. © 2012 AACC American Automatic Control Council).
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    Concurrent design of energy management and vehicle traction supervisory control algorithms for parallel hybrid electric vehicles
    (Institute of Electrical and Electronics Engineers Inc., 2016) Dokuyucu, H. I.; Cakmakci, M.
    In this paper, concurrent design of energy management (EM) and traction control algorithms for a vehicle equipped with a parallel hybrid powertrain is studied. This paper focuses on designing the two control algorithms together as one control design problem, which are traditionally considered separately. First, optimal control actions and operating points are obtained by applying dynamic programming (DP). Then, this information is used for developing a rule-based supervisory controller. Our objective is to minimize the fuel consumption and the wheel slip simultaneously. Two control problems are also solved separately and compared with the concurrent solution. Results show that promising benefits can be obtained by using the concurrent design approach rather than considering two control problems separately. Under the same conditions, the vehicle with the concurrent supervisory controller is 16% more efficient in fuel consumption and experiences 12% less wheel slip, assuming slippery road friction conditions. © 1967-2012 IEEE.
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    Cost and emission impacts of virtual power plant formation in plug-in hybrid electric vehicle penetrated networks
    (2013) Arslan, O.; Karasan, O. E.
    With increasing interest in alternative energy resources and technologies, mass penetration of PHEVs (plug-in hybrid vehicles) into the electricity grid and widespread utilization of DERs (distributed energy resources) are anticipated in the near future. As an aggregation unit, the VPP (virtual power plant) is introduced for load management and resource scheduling. In this article, we develop an energy management model for VPPs and analyze the cost and emission impacts of VPP formation and PHEV penetration. We conduct a case study for the state of California using real-world data from official resources. An average of 29.5% cost reduction and 79% CO2 and 83% NOx emission reductions are attained as shared benefits of consumers in the case study. Results are illustrative of opportunities that VPP formation can provide for the community. Sensitivity of the results to the DER costs and capacities, battery and gasoline prices are also analyzed. In addition, we prove that charging and discharging do not simultaneously occur in the solutions, which leads to a simplification in traditional energy management models.
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    Development of a supervisory controller for residential energy management problems
    (AACC, 2012-06) Akgün, Emre; Çakmakçı, Melih
    In recent years, the infrastructure that supplies energy to residential areas has started to evolve into a multi-source system, just like in automotive industry in which hybrid electric vehicles (HEVs) have been replacing conventional gasoline vehicles. Multi energy source systems considered as a potential solution for carbon emission problems despite their challenges in their operation due to increased complexity. In this paper, a control design approach successfully applied in the automotive industry is used to solve a residential energy management problem. First, a dynamic programming method is applied to obtain optimal control actions for the representative demand profiles and then by using these results, a causal supervisory controller is developed. It is found that the developed baseline controller performs 1-2% better daily in its initial form in terms of operational costs, compared to available heuristic strategies. © 2012 AACC American Automatic Control Council).
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    Energy management for age of information control in solar-powered IoT end devices
    (Springer, 2021-07) Aydin, A. K.; Akar, Nail
    In this paper, we propose several harvesting-aware energy management policies for solar-powered wireless IoT end devices that asynchronously send status updates for their surrounding environments to a network gateway device. For such devices, we aim at minimizing the average age of information (AoI) metric which has recently been investigated extensively for status update systems. The proposed energy management policies are obtained using discrete-time Markov chain-based modeling of the stochastic intra-day variations of the solar energy harvesting process in conjunction with the average reward Markov decision process formulation. With this approach, energy management policies are constructed by using the time of day and month of year information in addition to the instantaneous values of the age of information and the battery level. The effectiveness of the proposed energy management policies in terms of their capability to reduce the average AoI as well as improving upon the tail of the AoI distribution, is validated with empirical data for a wide range of system parameters.
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    Energy management in microgrids with plug-in electric vehicles, distributed energy resources and smart home appliances
    (Springer, Singapore, 2015) Arslan, Okan; Karaşan, Oya Ekin; Rajakaruna, S.; Shahnia, F.; Ghosh, A.
    Smart Grid is transforming the way energy is being generated and distributed today, leading to the development of environment-friendly, economic and efficient technologies such as plug-in electric vehicles (PEVs), distributed energy resources and smart appliances at homes. Among these technologies, PEVs pose both a risk by increasing the peak load as well as an opportunity for the existing energy management systems by discharging electricity with the help of Vehicle-to-grid (V2G) technology. These complications, together with the PEV battery degradation, compound the challenge in the management of existing energy systems. In this context, microgrids are proposed as an aggregation unit to smartly manage the energy exchange of these different state-of-the-art technologies. In this chapter, we consider a microgrid with a high level of PEV penetration into the transportation system, widespread utilization of smart appliances at homes, distributed energy generation and community-level electricity storage units. We propose a mixed integer linear programming energy management optimization model to schedule the charging and discharging times of PEVs, electricity storage units, and running times of smart appliances. Our findings show that simultaneous charging and discharging of PEV batteries and electricity storage units do not occur in model solutions due to system energy losses.
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    Energy management in plug-in hybrid electric vehicle penetrated networks
    (2016-04) Arslan, Okan
    With the introduction of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) into the transportation system, a new line of research has emerged in the literature that reconsiders existing problems from the electrified transportation point of view. In this context, our objective is to understand the challenges that arise with the emergence of PHEV technology through a series of essays. Due to their ability to use electricity and gasoline as sources of energy with di↵erent cost structures and limitations, PHEVs stand as both a challenge and an opportunity for the existing transportation systems. They provide transportation cost reductions by utilizing less gasoline, which in turn contribute to the environmental benefits. In this context, we addressed a practically important problem: ‘finding the minimum cost path for PHEVs’. We formally present this problem, show that it is NP-Complete and propose exact and heuristic solution techniques. Using these techniques, we investigate impacts of battery characteristics, driver preferences and road network features on travel costs of a PHEV for long-distance trips. Through this analysis, the location of charging stations is identified as one of the critical factors a↵ecting the costs. In this regard, we introduce another practically important problem: ‘Hybrid charging station location’. Di↵erent than existing approaches to the charging station location problems, we also consider PHEVs when locating stations. We propose a Benders Decomposition algorithm as an exact solution methodology, and accelerate the implementation by generating nondominated cuts. Finally, we analyze the cost and emission impacts of PHEV penetration into electricity networks with widespread adoption of distributed energy resources. Approaching PHEVs from a long-distance point of view, we introduced new problems and solution approaches to the literature. Our results show that by establishing an adequate level of the intercity charging station infrastructure, wellstudied benefits of electrified transportation in urban regions can be extended to long-distance trips.
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    Energy minimizing vehicle routing problem
    (Springer, 2007) Kara, İ.; Kara, Bahar Y.; Yetiş, M. K.
    This paper proposes a new cost function based on distance and load of the vehicle for the Capacitated Vehicle Routing Problem. The vehicle-routing problem with this new load-based cost objective is called the Energy Minimizing Vehicle Routing Problem (EMVRP). Integer linear programming formulations with O(n 2) binary variables and O(n2) constraints are developed for the collection and delivery cases, separately. The proposed models are tested and illustrated by classical Capacitated Vehicle Routing Problem (CVRP) instances from the literature using CPLEX 8.0.
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    Minimum cost path problem for Plug-in Hybrid Electric Vehicles
    (Elsevier Ltd, 2015) Arslan O.; Yildiz, B.; Karaşan O.E.
    We introduce a practically important and theoretically challenging problem: finding the minimum cost path for PHEVs in a road network with refueling and charging stations. We show that this problem is NP-complete and present a mixed integer quadratically constrained formulation, a discrete approximation dynamic programming heuristic, and a shortest path heuristic as solution methodologies. Practical applications of the problem in transportation and logistics, considering specifically the long-distance trips, are discussed in detail. Through extensive computational experiments, significant insights are provided. In addition to the charging infrastructure availability, a driver's stopping tolerance arises as another critical factor affecting the transportation costs. © 2015 Elsevier Ltd.