Journal articles: 'Battery optimisation'

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Yusof, M. S., S. F. Toha, N. A. Kamisan, N. N. W. N. Hashim, and M. A. Abdullah. "Battery Cell Balancing Optimisation for Battery Management System." IOP Conference Series: Materials Science and Engineering 184 (March 2017): 012021. http://dx.doi.org/10.1088/1757-899x/184/1/012021.

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Torquato, Matheus F., Kayalvizhi Lakshmanan, Natalia Narożańska, Ryan Potter, Alexander Williams, Fawzi Belblidia, Ashraf A. Fahmy, and Johann Sienz. "Cascade Optimisation of Battery Electric Vehicle Powertrains." Procedia Computer Science 192 (2021): 592–601. http://dx.doi.org/10.1016/j.procs.2021.08.061.

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Noack, Jens, Mike Wernado, Jens Ortner, and Karsten Pinkwart. "(Invited) Iron/Iron Redox Flow Battery Optimisation Studies." ECS Meeting Abstracts MA2022-02, no. 30 (October 9, 2022): 1095. http://dx.doi.org/10.1149/ma2022-02301095mtgabs.

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Due to the steadily increasing growth of renewable energies, the importance of stationary energy storage systems is growing significantly. A potentially very cheap alternative to lithium-ion and vanadium redox flow batteries are iron/iron redox flow batteries. Iron is an extremely inexpensive active material, thus enabling cheap energy storage solutions and perhaps batteries with very low investment costs while maintaining low toxicity and aggressiveness due to the moderate pH and relatively low potential of the positive electrode. An iron(II) salt solution serves as the initial solution and is oxidized to iron(III) at the positive electrode and reduced to elemental iron at the negative electrode during the charging process. One of the biggest problems is the formation of hydrogen at the iron electrode during the charging process at low pH values and the precipitation of iron(II) hydroxides from slightly acidic pH values [[i]]. When operating this type of battery, the negative electrode must be kept within a narrow pH window where no precipitation occurs and as little hydrogen as possible is evolved, which in turn significantly reduces battery life and efficiency. As part of a feasibility, different iron/iron redox flow batteries were constructed and their electrochemical properties were investigated. One of the most important components of the battery was the recombination cell, which allows hydrogen evolution to be reversed, thus significantly increasing the number of cycles. Different substrates for iron deposition were investigated, different membranes as well as different charging and discharging parameters of the battery. With the recombination cell, it was possible to complete up to one hundred cycles with long cycle times of 1 h charging time, and to calculate and compare efficiencies and other performance values. A kynol fabric achieved the best performance and all membranes investigated showed potential applications. An optimized battery achieved up to 70% energy efficiency at 12.5 mA/cm² and max. 47 mW/cm² power density at 75 mA/cm². [i] [1]L. W. Hruska, J. Electrochem. Soc. 1981, 128, 18. Figure 1

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Schweighofer, Lukas, Bernd Eschelmüller, Katja Fröhlich, Wilhelm Pfleging, and Franz Pichler. "Modelling and Optimisation of Laser-Structured Battery Electrodes." Nanomaterials 12, no. 9 (May 6, 2022): 1574. http://dx.doi.org/10.3390/nano12091574.

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An electrochemical multi-scale model framework for the simulation of arbitrarily three-dimensional structured electrodes for lithium-ion batteries is presented. For the parameterisation, the electrodes are structured via laser ablation, and the model is fit to four different, experimentally electrochemically tested cells. The parameterised model is used to optimise the parameters of three different pattern designs, namely linear, gridwise, and pinhole geometries. The simulations are performed via a finite element implementation in two and three dimensions. The presented model is well suited to depict the experimental cells, and the virtual optimisation delivers optimal geometrical parameters for different C-rates based on the respective discharge capacities. These virtually optimised cells will help in the reduction of prototyping cost and speed up production process parameterisation.

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Frieß, Benedikt, Thomas Soczka-Guth, Florian Hofbeck, and Franz Nietfeld. "Challenges in battery development basics and optimisation strategy." ATZelektronik worldwide 12, no. 6 (December 2017): 36–41. http://dx.doi.org/10.1007/s38314-017-0076-4.

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Jurčević, Jura, Ivan Pavić, Nikolina Čović, Denis Dolinar, and Davor Zoričić. "Estimation of Internal Rate of Return for Battery Storage Systems with Parallel Revenue Streams: Cycle-Cost vs. Multi-Objective Optimisation Approach." Energies 15, no. 16 (August 12, 2022): 5859. http://dx.doi.org/10.3390/en15165859.

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This paper assesses the profitability of battery storage systems (BSS) by focusing on the internal rate of return (IRR) as a profitability measure which offers advantages over other frequently used measures, most notably the net present value (NPV). Furthermore, this study proposes a multi-objective optimisation (MOO) approach to IRR estimation instead of relying on the simple linear optimisation and compares the results to the popular linear optimisation with battery cycle-cost penalty. The analysis is conducted under perfect foresight conditions by considering multiple revenue streams: arbitrage trading in the day-ahead and intraday markets, peak shaving, participating in the primary reserves market, and from photovoltaic (PV) power-generation unit. Data are collected for the German power market for 2017 and 2021. The results show that MOO approach yields similar IRR estimates to the cycle-cost model in 2017. However, higher market volatility and increased electricity prices in 2021 resulted in tangible differences. The analysis shows that, if such conditions are coupled with a low battery capacity price, the MOO method significantly outperforms the cycle-cost model. The effects of battery calendar lifetime and state of charge which decrease profitability are also considered. Nevertheless, a noticeable rise in profitability in 2021 relative to 2017 could provide enough compensation to address the issue of relatively poor viability track record.

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Akbar, Faraz. "Weight Optimisation of Electric Vehicle through Hybrid Structural Batteries." International Journal of Automotive and Mechanical Engineering 17, no. 4 (December 31, 2020): 8310–25. http://dx.doi.org/10.15282/ijame.17.4.2020.08.0628.

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This paper contributes towards the research and development campaign on the weight reduction of electric vehicles through the technology of structural composite batteries. Batteries are the key component and an integral part of electric vehicles which constitutes a major proportion of the vehicle’s weight. Most of the electric vehicle manufacturers use lithium-ion batteries which are in recent years have gone through a major development. The use of lithium-ion batteries within a carbon reinforced composite structure of the car has given rise to the concept of structural batteries where both the mechanical strength of the structure and the chemistry of the battery to be optimized. Various aspects of design in the formulation of the structural batteries are reviewed including material selection with respect to its electrical and mechanical requirements. In this research work, properties of carbon fiber are utilised which provide mechanical strength to the vehicle whilst be an efficient electrode for the lithium-ion structural batteries. The impacts of lithiation on the strength of the structure and charge time for the batteries are explored. Significant results of weight reduction have been achieved by formulating the structural battery for the roof of a passenger car having a 30 kW-hr battery. At 0.7 mm of active electrode thickness is designed within the roof structure, the roof can store 5.9 kW-hr of energy with the reduction of 56.5 kg in overall weight of the vehicle. The battery pack of 255 kg gets completely replaced by the structural composite battery because of its magnificent specific charge capacity at the active electrode with the thickness of 3.5 mm.

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Aycı, Doğukan, Ferhat Öğüt, Ulaş Özen, Bora Batuhan İşgör, and Sinan Küfeoğlu. "Energy Optimisation Models for Self-Sufficiency of a Typical Turkish Residential Electricity Customer of the Future." Energies 14, no. 19 (September 27, 2021): 6163. http://dx.doi.org/10.3390/en14196163.

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This paper utilises a two-stage demand response-enabled energy management algorithm for a typical Turkish self-sufficient living space. The proposed energy management model provides an additional gain in line with the goal of self-sufficiency by scheduling flexible loads and energy storage systems at home according to a static time of use tariff. The impact of load scheduling and battery optimisation were evaluated in the scope of self-sufficiency, economic gain and return on investment performances. According to the results, the proposed two-stage structure provided a net saving increase of 9.5% in the one-battery scenario, and it rises to 14% in the design with three batteries. On the other hand, when we inspect the energy management scenarios with the return on investment (ROI) calculations, we see that the single battery system has a higher ROI than the two or three battery systems due to the increased battery cost. Moreover, the ROI value, 13.9% without optimisation, increased to 15.3% in the proposed Home Energy Management System (HEMS) model. As can be seen from this calculation, intelligent management of batteries and flexible loads provided a 10% increase in ROI value.

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He, Yicheng, Kai Yang, Xiaoqing Wang, Haisong Huang, and Jiadui Chen. "Quality Prediction and Parameter Optimisation of Resistance Spot Welding Using Machine Learning." Applied Sciences 12, no. 19 (September 25, 2022): 9625. http://dx.doi.org/10.3390/app12199625.

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In a small sample welding test space, and to achieve online prediction and self-optimisation of process parameters for the resistance welding joint quality of power lithium battery packs, this paper proposes a welding quality prediction model. The model combines a chaos game optimisation algorithm (CGO) with the multi-output least-squares support vector regression machine (MLSSVR), and a multi-objective process parameter optimisation method based on a particle swarm algorithm. First, the MLSSVR model was constructed, and a hyperparameter optimisation strategy based on CGO was designed. Next, the welding quality was predicted using the CGO–MLSSVR prediction model. Finally, the particle swarm algorithm (PSO) was used to obtain the optimal welding process parameters. The experimental results show that the CGO–MLSSVR prediction model can effectively predict the positive and negative electrode nugget diameters, and tensile shear loads, with root mean square errors of 0.024, 0.039, and 5.379, respectively, which is better than similar methods. The average relative error in weld quality for the optimal welding process parameters is within 4%, and the proposed method has a good application value in the resistance spot welding of power lithium battery packs.

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Jeffs, James, Truong Quang Dinh, Widanalage Dhammika Widanage, Andrew McGordon, and Alessandro Picarelli. "Optimisation of Direct Battery Thermal Management for EVs Operating in Low-Temperature Climates." Energies 13, no. 22 (November 16, 2020): 5980. http://dx.doi.org/10.3390/en13225980.

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Electric vehicles (EVs) experience a range reduction at low temperatures caused by the impact of cabin heating and a reduction in lithium ion performance. Heat pump equipped vehicles have been shown to reduce heating ventilation and air conditioning (HVAC) consumption and improve low ambient temperature range. Heating the electric battery, to improve its low temperature performance, leads to a reduction in heat availability for the cabin. In this paper, dynamic programming is used to find the optimal battery heating trajectory which can optimise the vehicle’s control for either cabin comfort or battery performance and, therefore, range. Using the strategy proposed in this research, a 6.2% increase in range compared to no battery heating and 5.5% increase in thermal comfort compared to full battery heating was achieved at an ambient temperature at −7 °C.

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Tikkiwal, Vinay Anand, Sajai Vir Singh, and Hari Om Gupta. "Multi-objective optimisation of a grid-connected hybrid PV-battery system considering battery degradation." International Journal of Sustainable Engineering 14, no. 6 (October 6, 2021): 1769–79. http://dx.doi.org/10.1080/19397038.2021.1982064.

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Chen, N. A., Fei Xiong, Fengchong Lan, and Songsong Kuang. "Crush simulation and optimisation study of power battery pack." International Journal of Vehicle Safety 11, no. 1 (2019): 37. http://dx.doi.org/10.1504/ijvs.2019.101304.

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Othaganont, Pongpun, Francis Assadian, and Daniel J. Auger. "Multi-objective optimisation for battery electric vehicle powertrain topologies." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 231, no. 8 (October 6, 2016): 1046–65. http://dx.doi.org/10.1177/0954407016671275.

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Electric vehicles are becoming more popular in the market. To be competitive, manufacturers need to produce vehicles with a low energy consumption, a good range and an acceptable driving performance. These are dependent on the choice of components and the topology in which they are used. In a conventional gasoline vehicle, the powertrain topology is constrained to a few well-understood layouts; these typically consist of a single engine driving one axle or both axles through a multi-ratio gearbox. With electric vehicles, there is more flexibility, and the design space is relatively unexplored. In this paper, we evaluate several different topologies as follows: a traditional topology using a single electric motor driving a single axle with a fixed gear ratio; a topology using separate motors for the front axle and the rear axle, each with its own fixed gear ratio; a topology using in-wheel motors on a single axle; a four-wheel-drive topology using in-wheel motors on both axes. Multi-objective optimisation techniques are used to find the optimal component sizing for a given requirement set and to investigate the trade-offs between the energy consumption, the powertrain cost and the acceleration performance. The paper concludes with a discussion of the relative merits of the different topologies and their applicability to real-world passenger cars.

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Andal C., Kothai, and Jayapal R. "Improved GA based power and cost management system in a grid-associated PV-wind system." International Journal of Power Electronics and Drive Systems (IJPEDS) 12, no. 4 (December 1, 2021): 2531. http://dx.doi.org/10.11591/ijpeds.v12.i4.pp2531-2544.

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Renewable hybrids play an essential part in assisting India with quickening the decarbonisation of power production and lowering power production expense in the medium term. PV and wind energy are complementary to each other, making the system to generate electricity almost throughout the year. In this paper, a grid-associated PV-wind energy system tied with a battery is analysed. PV, wind, grid and battery are the sources to be effectively scheduled for uninterrupted power and cost minimisation. Energy management controllers use optimisation strategies for effective utilisation of sources and cost minimisation. The methodologies are detailed as optimisation problems. Limiting the household energy cost is considered as objective, and the delivery ratio of power offered to the grid and utilised locally is treated as the optimisation variable. In this paper, an improved genetic algorithm is proposed to solve the formulated nonlinear optimisation problems. The time-of-use tariff is becoming popular in India; therefore, this article analyses the improved genetic algorithm based intelligent power and cost management system under time-of-use tariff. Using MATLAB, the proposed approach's performance is presented with the comparative analysis of conventional self-made for self-consumed and rest for sale mode and genetic algorithm-based energy management controller.

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Sousa, Joaquim Vasconcelos Reinolds de, and Pedro Gamboa. "UAV trajectory optimisation with limited onboard energy budget." Aircraft Engineering and Aerospace Technology 94, no. 2 (October 28, 2021): 255–67. http://dx.doi.org/10.1108/aeat-01-2021-0015.

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Purpose The purpose of this paper is to generate optimised trajectories for an unmanned aerial vehicle (UAV) during a forest fire detection mission. It is assumed that the UAV flies 3D curvature-constrained Dubins manoeuvres and has a limited amount of battery energy that prevents it from covering the entire search area in a single trip. Design/methodology/approach In this paper, the search area is discretised into a grid of multiple targets, and each target assigned with a score that is proportional to the time elapsed since the last UAV visit. This problem, known as Dubins Airplane Orienteering Problem, consists of finding the number and order of targets to visit and the UAV heading at each target that maximises the total trip score without exceeding the UAV battery energy. The solution is found using the Randomised Variable Neighbourhood Search metaheuristic. All target scores are updated after each trajectory generation according to the elapsed time since the last UAV visit. Findings The proposed approach produced feasible results when generating optimised trajectories for a fire detection mission context where energy battery constraints are important. Practical implications The authors carry out the planning of UAV missions with limited amounts of onboard energy such as a real fire detection mission using a single electric propulsion and fixed-wing UAV. Originality/value This paper introduces an energy-based approach to the Dubins Airplane Orienteering Problem, which takes into account the UAV performance and energy budget when generating optimised trajectories.

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Hesse, Holger, Volkan Kumtepeli, Michael Schimpe, Jorn Reniers, David Howey, Anshuman Tripathi, Youyi Wang, and Andreas Jossen. "Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming." Energies 12, no. 6 (March 14, 2019): 999. http://dx.doi.org/10.3390/en12060999.

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To achieve maximum profit by dispatching a battery storage system in an arbitrage operation, multiple factors must be considered. While revenue from the application is determined by the time variability of the electricity cost, the profit will be lowered by costs resulting from energy efficiency losses, as well as by battery degradation. In this paper, an optimal dispatch strategy is proposed for storage systems trading on energy arbitrage markets. The dispatch is based on a computationally-efficient implementation of a mixed-integer linear programming method, with a cost function that includes variable-energy conversion losses and a cycle-induced battery capacity fade. The parametrisation of these non-linear functions is backed by in-house laboratory tests. A detailed analysis of the proposed methods is given through case studies of different cost-inclusion scenarios, as well as battery investment-cost scenarios. An evaluation with a sample intraday market data set, collected throughout 2017 in Germany, offers a potential monthly revenue of up to 8762 EUR/MWh cap installed capacity, without accounting for the costs attributed to energy losses and battery degradation. While this is slightly above the revenue attainable in a reference application—namely, primary frequency regulation for the same sample month (7716 EUR/MWh cap installed capacity)—the situation changes if costs are considered: The optimisation reveals that losses in battery ageing and efficiency reduce the attainable profit by up to 36% for the most profitable arbitrage use case considered herein. The findings underline the significance of considering both ageing and efficiency in battery system dispatch optimisation.

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Martinez-Laserna, Egoitz, Victor Herrera, Iñigo Gandiaga, Aitor Milo, Elixabet Sarasketa-Zabala, and Haizea Gaztañaga. "Li-Ion Battery Lifetime Model’s Influence on the Economic Assessment of a Hybrid Electric Bus’s Operation." World Electric Vehicle Journal 9, no. 2 (July 26, 2018): 28. http://dx.doi.org/10.3390/wevj9020028.

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The present paper is focused on the evaluation of the economic influence of a battery lifetime model upon the optimal sizing and energy management strategy of a dual energy storage system (ESS) composed of Lithium-ion batteries and supercapacitors. The operation of a Hybrid Bus is taken as a case study in order to evaluate the effects of battery lifetime models’ accuracy on ESS sizing and operation in a heavy-duty application. For this purpose, two different lifetime models (a Wöhler-curve-based model and a semi-empirical model) were applied in the multi-objective optimisation of a hybrid electric urban bus. Differences up to ca. 8% on the daily operation costs and ca. 25% on the dual ESS costs were estimated depending on the lifetime model considered for the optimisation.

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Hartmann, Matthias, Martin Roschitz, and Ziad Khalil. "Enhanced Battery Pack for Electric Vehicle: Noise Reduction and Increased Stiffness." Materials Science Forum 765 (July 2013): 818–22. http://dx.doi.org/10.4028/www.scientific.net/msf.765.818.

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Vibration and the noise through vibration have always been major topics for the design of vehicles. An electric vehicle presents different challenges to a conventional driven vehicle, as a combustion engine produces different exciter frequencies. In this work, the Finite Element (FE) Optimisation software OptiStruct [1] was used to optimise the battery pack design to raise the natural frequencies of the battery housing above the range of model vehicle exciter frequencies. The new design increased the stiffness of the battery pack. Additionally, there was a reduction in wall thickness and a corresponding weight reduction of almost 20%.

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Tohidi, Yaser, and Madeleine Gibescu. "Stochastic optimisation for investment analysis of flow battery storage systems." IET Renewable Power Generation 13, no. 4 (January 17, 2019): 555–62. http://dx.doi.org/10.1049/iet-rpg.2018.5788.

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J. Auger, Daniel, Maxime F. Groff, Ganesh Mohan, Stefano Longo, and Francis Assadian. "Impact of Battery Ageing on an Electric Vehicle Powertrain Optimisation." Journal of Sustainable Development of Energy, Water and Environment Systems 2, no. 4 (December 2014): 350–61. http://dx.doi.org/10.13044/j.sdewes.2014.02.0028.

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Glavin, M. E., and W. G. Hurley. "Optimisation of a photovoltaic battery ultracapacitor hybrid energy storage system." Solar Energy 86, no. 10 (October 2012): 3009–20. http://dx.doi.org/10.1016/j.solener.2012.07.005.

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Tenno, R., and E. Nefedov. "Electrolyte depletion control laws for lead-acid battery discharge optimisation." Journal of Power Sources 270 (December 2014): 658–67. http://dx.doi.org/10.1016/j.jpowsour.2014.07.154.

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Zhang, Han, Jibin Yang, Jiye Zhang, Pengyun Song, and Ming Li. "Optimal energy management of a fuel cell-battery-supercapacitor-powered hybrid tramway using a multi-objective approach." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 234, no. 5 (May 15, 2019): 511–23. http://dx.doi.org/10.1177/0954409719849804.

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Achieving an optimal operating cost is a challenge for the development of hybrid tramways. In the past few years, in addition to fuel costs, the lifespan of the power source is being increasingly considered as an important factor that influences the operating cost of a tramway. In this work, an optimal energy management strategy based on a multi-mode strategy and optimisation algorithm is described for a high-power fuel cell hybrid tramway. The objective of optimisation is to decrease the operating costs under the conditions of guaranteeing tramway performance. Besides the fuel costs, the replacement cost and initial investment of all power units are also considered in the cost model, which is expressed in economic terms. Using two optimisation algorithms, a multi-population genetic algorithm and an artificial fish swarm algorithm, the hybrid system's power targets for the energy management strategy were acquired using the multi-objective optimisation. The selected case study includes a low-floor light rail vehicle, and experimental validations were performed using a hardware-in-the-loop workbench. The results testify that an optimised energy management strategy can fulfil the operational requirements, reduce the daily operation costs and improve the efficiency of the fuel cell system for a hybrid tramway.

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Strachan, Jyah, Lu Chen, Thomas Ellis, Anthony Masters, and Thomas Maschmeyer. "Influence of Crystal Disorder in MoS2 Cathodes for Secondary Hybrid Mg-Li Batteries." Australian Journal of Chemistry 74, no. 11 (2021): 819. http://dx.doi.org/10.1071/ch21187.

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The full extent to which the electrochemical properties of MoS2 electrodes are influenced by their morphological characteristics, such as crystalline disorder, remains unclear. Here, we report that disorder introduced by ball-milling decreases the Faradaic component of cell capacity and leads to increasingly pseudo-capacitive behaviour. After high temperature annealing, a more battery-like character of the cell is restored, consistent with a decrease in disorder. These findings aid the optimisation of MoS2 electrodes, which show promise in several battery technologies.

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Larrañaga-Ezeiza, Manex, Gorka Vertiz Navarro, Igor Galarza Garmendia, Peru Fernandez Arroiabe, Manex Martinez-Aguirre, and Joanes Berasategi Arostegui. "Parametric Optimisation of a Direct Liquid Cooling–Based Prototype for Electric Vehicles Focused on Pouch-Type Battery Cells." World Electric Vehicle Journal 13, no. 8 (August 9, 2022): 149. http://dx.doi.org/10.3390/wevj13080149.

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In this work, a numerical optimisation process is applied to improve the fluid dynamical aspect of an innovative direct liquid cooling strategy for lithium-ion–based HEV/EV. First, the thermofluidic numerical model of the battery cell defined by means of CFD computational tools was validated with experimental tests. Then, a comparison between different flow patterns was developed to analyse the influence of the fluid distribution geometry. Finally, a parametric multi-objective optimisation process was implemented arranged by a two-level full factorial design. Considering as input variables the height of the fluid, the number of cooling channels, the number of distributors, and the flow rate, the optimal relationship between the thermal performance of the battery cell, the volumetric energy density of the system, and the power consumption of the strategy was obtained. As a result, the energy density of the system was maximised, and the power consumption was reduced while keeping the cell temperature within the optimal range.

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Mohseni, Soheil, and Alan C. Brent. "A Metaheuristic-Based Micro-Grid Sizing Model with Integrated Arbitrage-Aware Multi-Day Battery Dispatching." Sustainability 14, no. 19 (October 10, 2022): 12941. http://dx.doi.org/10.3390/su141912941.

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Rule-based micro-grid dispatch strategies have received significant attention over the last two decades. However, a recent body of literature has conclusively shown the benefits of operational scheduling optimisation while optimally sizing micro-grids. This is commonly referred to as micro-grid design and dispatch co-optimisation (MGDCO). However, as far as can be ascertained, all the existing MGDCO models in the literature consider a 24-h-resolved day-ahead timeframe for the associated optimal energy scheduling processes. That is, intelligent, look-ahead energy dispatch strategies over multi-day timeframes are generally absent from the wider relevant literature. In response, this paper introduces a novel MGDCO modelling framework that integrates an arbitrage-aware linear programming-based multi-day energy dispatch strategy into the standard metaheuristic-based micro-grid investment planning processes. Importantly, the model effectively extends the mainstream energy scheduling optimisation timeframe in the micro-grid investment planning problems by producing optimal dispatch solutions that are aware of scenarios over three days. Based on the numeric simulation results obtained from a test-case micro-grid, the effectiveness of the proposed optimisation-based dispatch strategy in the micro-grid sizing processes is verified, while retaining the computational tractability. Specifically, comparing the proposed investment planning framework, which uses the formulated 72-h dispatch strategies, with the business-as-usual MGDCO methods has demonstrated that it can reduce the micro-grid’s whole-life cost by up to 8%. Much of the outperformance of the proposed method can be attributed to the effective use of the behind-the-meter Li-ion battery storage, which improves the overall system flexibility.

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Singh, Pushpendra, Nand Kishor Meena, Jin Yang, Shree Krishna Bishnoi, Eduardo Vega-Fuentes, and Chengwei Lou. "Modified Dragonfly Optimisation for Distributed Energy Mix in Distribution Networks." Energies 14, no. 18 (September 10, 2021): 5690. http://dx.doi.org/10.3390/en14185690.

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This article presents a two-stage optimization model aiming to determine optimal energy mix in distribution networks, i.e., battery energy storage, fuel cell, and wind turbines. It aims to alleviate the impact of high renewable penetration on the systems. To solve the proposed complex optimization model, a standard variant of the dragonfly algorithm (DA) has been improved and then applied to find the optimal mix of distributed energy resources. The suggested improvements are validated before their application. A heuristic approach has also been introduced to solve the second stage problem that determines the optimal power dispatch of battery energy storage as per the size suggested by the first stage. The proposed framework was implemented on a benchmark 33-bus and a practical Indian 108-bus distribution network over different test cases. The proposed model for energy mix and modified DA technique has significantly enhanced the operational performance of the network in terms of average annual energy loss reduction, node voltage profiles, and demand fluctuation caused by renewables.

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B, Suresh G., and D. Mathivanan. "Heuristic Based Power Consumption Minimisation and Optimisation on Smartphones." Indonesian Journal of Electrical Engineering and Computer Science 9, no. 2 (February 1, 2018): 345. http://dx.doi.org/10.11591/ijeecs.v9.i2.pp345-346.

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In the direction of capable save the energy of battery life in Smartphone accurate with sensible influence form of Wi-Fi data communication in infrastructure mode. The network environment parameters like still time in a 3G system the network throughput and the convey pattern have been accepted all through measurement study the collective impact of an issue has not been systematical.

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Liu, Yang, Matthew Rowe, William Holderbaum, and Ben Potter. "A novel battery network modelling using constraint differential evolution algorithm optimisation." Knowledge-Based Systems 99 (May 2016): 10–18. http://dx.doi.org/10.1016/j.knosys.2016.01.019.

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Cristóbal-Monreal, Iván R., and Rodolfo Dufo-López. "Optimisation of photovoltaic–diesel–battery stand-alone systems minimising system weight." Energy Conversion and Management 119 (July 2016): 279–88. http://dx.doi.org/10.1016/j.enconman.2016.04.050.

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Marcelino, Carolina, Manuel Baumann, Leonel Carvalho, Nelson Chibeles-Martins, Marcel Weil, Paulo Almeida, and Elizabeth Wanner. "A combined optimisation and decision-making approach for battery-supported HMGS." Journal of the Operational Research Society 71, no. 5 (April 20, 2019): 762–74. http://dx.doi.org/10.1080/01605682.2019.1582590.

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Sachs, Julia, Kevin Tom, and Oliver Sawodny. "Optimisation of real-time control for hybrid diesel–PV–battery systems." International Journal of Sustainable Energy 36, no. 2 (January 8, 2015): 124–41. http://dx.doi.org/10.1080/14786451.2014.999072.

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Kies, Alexander. "Joint optimisation of arbitrage profits and battery life degradation for grid storage application of battery electric vehicles." Journal of Physics: Conference Series 977 (February 2018): 012005. http://dx.doi.org/10.1088/1742-6596/977/1/012005.

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Frydrychowicz-Jastrzębska, Grażyna. "Maximum power point tracking in photovoltaic systems." ITM Web of Conferences 28 (2019): 01021. http://dx.doi.org/10.1051/itmconf/20192801021.

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The subject of the analysis was the optimisation of interoperation between the photovoltaic battery (PV) and DC motor, which drives a fan, with respect to the maximum efficiency of conversion of the electric energy into mechanical energy. Based on the block diagram, a mathematical model of this circuit was developed to ensure the mutual matching between the Maximum Power Point (MPP) of the battery and the receiver operation point. A computer simulation of the battery characteristics was conducted taking into account the changing MPP location on the characteristic vs. changes in solar radiation and temperature. The issue was considered for the optimal motor excitation coefficient, both changing and averaged in time. The energy conversion efficiency was determined for selected PV modules, as well as time.

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Yang, Liunan, Massimiliano Gobbi, Gianpiero Mastinu, Giorgio Previati, and Federico Ballo. "Multi-Disciplinary Optimisation of Road Vehicle Chassis Subsystems." Energies 15, no. 6 (March 16, 2022): 2172. http://dx.doi.org/10.3390/en15062172.

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Two vehicle chassis design tasks were solved by decomposition-based multi-disciplinary optimisation (MDO) methods, namely collaborative optimisation (CO) and analytical target cascading (ATC). A passive suspension system was optimised by applying both CO and ATC. Multiple parameters of the spring and damper were selected as design variables. The discomfort, road holding, and total mass of the spring–damper combination were the objective functions. An electric vehicle (EV) powertrain design problem was considered as the second test case. Energy consumption and gradeability were optimised by including the design of the electric motor and the battery pack layout. The standard single-level all-in-one (AiO) multi-objective optimisation method was compared with ATC and CO methods. AiO methods showed some limitations in terms of efficiency and accuracy. ATC proved to be the best choice for the design problems presented in this paper, since it provided solutions with good accuracy in a very efficient way. The proposed investigation on MDO methods can be useful for designers, to choose the proper optimisation approach, while solving complex vehicle design problems.

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Rahat, Alma A. M., Richard M. Everson, and Jonathan E. Fieldsend. "Hybrid Evolutionary Approaches to Maximum Lifetime Routing and Energy Efficiency in Sensor Mesh Networks." Evolutionary Computation 23, no. 3 (September 2015): 481–507. http://dx.doi.org/10.1162/evco_a_00151.

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Mesh network topologies are becoming increasingly popular in battery-powered wireless sensor networks, primarily because of the extension of network range. However, multihop mesh networks suffer from higher energy costs, and the routing strategy employed directly affects the lifetime of nodes with limited energy resources. Hence when planning routes there are trade-offs to be considered between individual and system-wide battery lifetimes. We present a multiobjective routing optimisation approach using hybrid evolutionary algorithms to approximate the optimal trade-off between the minimum lifetime and the average lifetime of nodes in the network. In order to accomplish this combinatorial optimisation rapidly, our approach prunes the search space using k-shortest path pruning and a graph reduction method that finds candidate routes promoting long minimum lifetimes. When arbitrarily many routes from a node to the base station are permitted, optimal routes may be found as the solution to a well-known linear program. We present an evolutionary algorithm that finds good routes when each node is allowed only a small number of paths to the base station. On a real network deployed in the Victoria & Albert Museum, London, these solutions, using only three paths per node, are able to achieve minimum lifetimes of over 99% of the optimum linear program solution’s time to first sensor battery failure.

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Mosca, V., S. Karpuk, A. Sudhi, C. Badrya, and A. Elham. "Multidisciplinary design optimisation of a fully electric regional aircraft wing with active flow control technology." Aeronautical Journal 126, no. 1298 (October 28, 2021): 730–54. http://dx.doi.org/10.1017/aer.2021.101.

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AbstractThe German research Cluster of Excellence SE2A (Sustainable and Energy Efficient Aviation) is investigating different technologies to be implemented in the following decades, to achieve more efficient air transportation. This paper studies the Hybrid Laminar Flow Control (HLFC) using boundary layer suction for drag reduction, combined with other technologies for load and structural weight reduction and a novel full-electric propulsion system. A multidisciplinary design optimisation framework is presented, enabling physics-based analysis and optimisation of a fully electric aircraft wing equipped with HLFC technologies and load alleviation, and new structures and materials. The main focus is on simulation and optimisation of the boundary layer suction and its influence on wing design and optimisation. A quasi three-dimensional aerodynamic analysis is used for drag estimation of the wing. The tool executes the aerofoil analysis using XFOILSUC, which provides accurate drag estimation through boundary layer suction. The optimisation is based on a genetic algorithm for maximum take-off weight (MTOW) minimisation. The optimisation results show that the active flow control applied on the optimised geometry results in more than 45% reduction in aircraft drag coefficient, compared to the same geometry without HLFC technology. The power absorbed for the HLFC suction system implies a battery mass variation lower than 2%, considering the designed range as top-level requirement (TLR).

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Ufert, M., and B. Bäker. "Battery Ageing as Part of the System Design of Battery Electric Urban Bus Fleets." Science & Technique 19, no. 1 (February 5, 2020): 12–19. http://dx.doi.org/10.21122/2227-1031-2020-19-1-12-19.

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The lifetime of traction battery systems is an essential feature of the economy of battery electric urban bus fleets. This paper presents a model for the analysis and prediction of the lifetime of urban electric bus batteries. The parameterization of the model is based on laboratory measurements. The empirical ageing model is an integral part of a three-stage battery model, which in turn is an important component of the methodology for the overall system design, evaluation and optimisation of battery electric urban bus fleets. In an equidistant closed simulation loop, the electrical and thermal loads of the traction battery are determined, which are then used in the ageing model to calculate the SOH (state of health) of the battery. The closed simulation loop also considers the effects of a constantly changing SOH on the driving dynamics of the vehicles. The model for lifetime analysis and prognosis is presented in the paper, placed in the context of the overall system design and demonstrated by means of a practice-oriented example. The results show that the optimal system design depends, among other things, on whether an ageing simulation was used. Taking battery aging into account, system costs in the example presented can be reduced by up to 17 %.

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Skoglund, Ida E. U., Mette Rostad, and Kasper E. Thorvaldsen. "Impact of shared battery energy storage system on total system costs and power peak reduction in commercial buildings." Journal of Physics: Conference Series 2042, no. 1 (November 1, 2021): 012108. http://dx.doi.org/10.1088/1742-6596/2042/1/012108.

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Abstract The power system is experiencing an increasing share of renewable and intermittent energy production and increasing electrification. However, these changes are creating high power peaks, are straining the grid and call for expensive investments in expansions and improvements. This paper examines how the operational strategy of shared battery energy storage systems (s-BESS) can address these issues for commercial buildings with relatively high power peaks. Due to the uncertainty in long-term costs when subject to a measured peak (MP) grid tariff, the scheduling of the battery is optimised with a receding horizon control algorithm. The optimisation model is used on a Norwegian real-life case study to find the best possible configuration with an already existing battery. Although current Norwegian regulations challenge the possibility for shared metering and billing for a s-BESS configuration, the results show that the total system cost was reduced by 19.2% compared to no battery. The community peak was reduced by 17.8% compared to no battery and 6.22-17.5% compared to individual storage, which indicates that s-BESS is of value for the DSO as well.

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Fan, Fulin, Giorgio Zorzi, David Campos-Gaona, and John Nwobu. "Wind-Plus-Battery system optimisation for frequency response service: The UK perspective." Electric Power Systems Research 211 (October 2022): 108400. http://dx.doi.org/10.1016/j.epsr.2022.108400.

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Jayawardana, Asanga, Ashish P. Agalgaonkar, Duane A. Robinson, and Massimo Fiorentini. "Optimisation framework for the operation of battery storage within solar‐rich microgrids." IET Smart Grid 2, no. 4 (June 26, 2019): 504–13. http://dx.doi.org/10.1049/iet-stg.2019.0084.

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Lloyd, J. J., C. J. Taylor, R. S. Lawson, and R. A. Shields. "Comparison of local and global optimisation techniques for diffusion battery data analysis." Journal of Aerosol Science 28, no. 5 (July 1997): 821–31. http://dx.doi.org/10.1016/s0021-8502(96)00464-8.

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Mason, I. G., and A. J. V. Miller. "Energetic and economic optimisation of islanded household-scale photovoltaic-plus-battery systems." Renewable Energy 96 (October 2016): 559–73. http://dx.doi.org/10.1016/j.renene.2016.03.048.

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Mariaud, Arthur, Salvador Acha, Ned Ekins-Daukes, Nilay Shah, and Christos N. Markides. "Integrated optimisation of photovoltaic and battery storage systems for UK commercial buildings." Applied Energy 199 (August 2017): 466–78. http://dx.doi.org/10.1016/j.apenergy.2017.04.067.

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Hossain, Md Alamgir, Hemanshu Roy Pota, Stefano Squartini, Forhad Zaman, and Josep M. Guerrero. "Energy scheduling of community microgrid with battery cost using particle swarm optimisation." Applied Energy 254 (November 2019): 113723. http://dx.doi.org/10.1016/j.apenergy.2019.113723.

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Liu, Weijia, Fushuan Wen, Yusheng Xue, Zhenzhi Lin, and Lei Sun. "Multi-objective restoration optimisation of power systems with battery energy storage systems." IET Generation, Transmission & Distribution 10, no. 7 (May 5, 2016): 1749–57. http://dx.doi.org/10.1049/iet-gtd.2015.0434.

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Fan, Fulin, Giorgio Zorzi, David Campos-Gaona, Graeme Burt, Olimpo Anaya-Lara, John Nwobu, and Ander Madariaga. "Sizing and Coordination Strategies of Battery Energy Storage System Co-Located with Wind Farm: The UK Perspective." Energies 14, no. 5 (March 6, 2021): 1439. http://dx.doi.org/10.3390/en14051439.

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The rapid development and growth of battery storage have heightened an interest in the co-location of battery energy storage systems (BESS) with renewable energy projects which enables the stacking of multiple revenue streams while reducing connection charges of BESS. To help wind energy industries better understand the coordinated operation of BESS and wind farms and its associated profits, this paper develops a simulation model to implement a number of coordination strategies where the BESS supplies enhanced frequency response (EFR) service and enables the time shift of wind generation based on the UK perspective. The proposed model also simulates the degradation of Lithium-Ion battery and incorporates a state of charge (SOC) dependent limit on the charge rate derived from a constant current-constant voltage charging profile. In addition, a particle swarm optimisation-based battery sizing algorithm is developed here on the basis of the simulation model to determine the optimal size of the co-located BESS along with SOC-related strategy variables that maximise the net present value of the wind + BESS system at the end of the EFR contract.

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Kahwash, Fadi, Basel Barakat, Ahmad Taha, Qammer H. Abbasi, and Muhammad Ali Imran. "Optimising Electrical Power Supply Sustainability Using a Grid-Connected Hybrid Renewable Energy System—An NHS Hospital Case Study." Energies 14, no. 21 (October 29, 2021): 7084. http://dx.doi.org/10.3390/en14217084.

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This study focuses on improving the sustainability of electrical supply in the healthcare system in the UK, to contribute to current efforts made towards the 2050 net-zero carbon target. As a case study, we propose a grid-connected hybrid renewable energy system (HRES) for a hospital in the south-east of England. Electrical consumption data were gathered from five wards in the hospital for a period of one year. PV-battery-grid system architecture was selected to ensure practical execution through the installation of PV arrays on the roof of the facility. Selection of the optimal system was conducted through a novel methodology combining multi-objective optimisation and data forecasting. The optimisation was conducted using a genetic algorithm with two objectives (1) minimisation of the levelised cost of energy and (2) CO2 emissions. Advanced data forecasting was used to forecast grid emissions and other cost parameters at two year intervals (2023 and 2025). Several optimisation simulations were carried out using the actual and forecasted parameters to improve decision making. The results show that incorporating forecasted parameters into the optimisation allows to identify the subset of optimal solutions that will become sub-optimal in the future and, therefore, should be avoided. Finally, a framework for choosing the most suitable subset of optimal solutions was presented.

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Edla, Mahesh, Deguchi Mikio, Iman Izadgoshasb, M. A. Parvez Mahmud, and Abbas Z. Kouzani. "Self-powered boost-converter for power optimisation and piezo garden lights." Smart Materials and Structures 31, no. 4 (March 11, 2022): 045021. http://dx.doi.org/10.1088/1361-665x/ac58d3.

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Abstract This study gives a thorough model for a small vibration powered piezoelectric device (PD) and analysis modes of operation and control of a self-powered boost converter circuit (SPBC) for the goal of tracking the PD’s finest functioning points. The concept defines the power dependency of the PD on mechanical excitation and frequency, and it aids in the design of load behaviour for power optimisation. With a fundamental control circuit, the electrical nature of the input (i.e. PD) of an SPBC circuit in the discontinuous current mode is found to be in perfect configuration with the studied optimisation requirements. The performance of the proposed SPBC circuit is studied in terms of both simulation and experiment. Firstly, the performance of the SPBC on optimisation of the PD is investigated using a mechanical shaker. Then, the proposed circuit’s ability to charge a battery, which can be used in piezo garden lights with low-frequency applicability, is also investigated. The proposed circuit and control can also be utilised to optimise electromagnetic applications.

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Nguyen, N. V., J. W. Lee, M. Tyan, and D. Lee. "Possibility-Based Multidisciplinary Optimisation For Electric-Powered Unmanned Aerial Vehicle Design." Aeronautical Journal 119, no. 1221 (November 2015): 1397–414. http://dx.doi.org/10.1017/s0001924000011313.

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AbstractThis paper describes a possibility-based multidisciplinary optimisation for electric-powered unmanned aerial vehicles (UAVs) design. An in-house integrated UAV (iUAV) analysis program that uses an electric-powered motor was developed and validated by a Predator A configuration for aerodynamics, weight, and performance parameters. An electric-powered propulsion system was proposed to replace a piston engine and fuel with an electric motor, power controllers, and battery from an eco-system point of view. Moreover, an in-house Possibility-Based Design Optimisation (iPBDO) solver was researched and developed to effectively handle uncertainty variables and parameters and to further shift constraints into a feasible design space. A sensitivity analysis was performed to reduce the dimensions of design variables and the computational load during the iPBDO process. Maximising the electric-powered UAV endurance while solving the iPBDO yields more conservative, but more reliable, optimal UAV configuration results than the traditional deterministic optimisation approach. A high fidelity analysis was used to demonstrate the effectiveness of the process by verifying the accuracy of the optimal electric-powered UAV configuration at two possibility index values and a baseline.

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Journal articles on the topic 'Battery optimisation'

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