On Battery Management Strategies in Multi-agent Microgrid Management

2017 ◽  
pp. 191-202 ◽  
Author(s):  
Roozbeh Morsali ◽  
Sajad Ghorbani ◽  
Ryszard Kowalczyk ◽  
Rainer Unland
Keyword(s):  
Management Strategies ◽  
Battery Management ◽  
Multi Agent

Exploring management strategies for community-based forests using multi-agent systems: A case study in Palawan, Philippines

2009 ◽  
Vol 90 (11) ◽  
pp. 3607-3615 ◽  
Author(s):  
Paolo C. Campo ◽  
Guillermo A. Mendoza ◽  
Philippe Guizol ◽  
Teodoro R. Villanueva ◽  
François Bousquet
Keyword(s):  
Management Strategies ◽  
Multi Agent Systems ◽  
Community Based ◽  
Agent Systems ◽  
Multi Agent

scholarly journals En-Route Battery Management and a Mixed Network Equilibrium Problem Based on Electric Vehicle Drivers’ En-Route Recharging Behaviors

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4061
Author(s):  
Kai Liu ◽  
Sijia Luo ◽  
Jing Zhou
Keyword(s):  
Electric Vehicle ◽  
Equilibrium Model ◽  
Transportation Network ◽  
Management Strategies ◽  
Safety Margin ◽  
User Equilibrium ◽  
Network Equilibrium ◽  
Battery Management ◽  
Battery Safety ◽  
Safety Margins

With the rapidly increasing number of electric vehicle users, in many urbans transport networks, there are mixed traffic flows (i.e., electric vehicles and gasoline vehicles). However, limited by driving ranges and long battery recharging, the battery electric vehicle (BEV) drivers’ route choice behaviors are inevitably affected. This paper assumes that in a transportation network, when BEV drivers are traveling between their original location and destinations, they tend to select the path with the minimal driving times and recharging time, and ensure that the remaining charge is not less than their battery safety margin. In contrast, gasoline vehicle drivers tend to select the path with the minimal driving time. Thus, by considering BEV drivers’ battery management strategies, e.g., battery safety margins and en-route recharging behaviors, this paper developed a mixed user equilibrium model to describe the resulting network equilibrium flow distributions. Finally, a numerical example is presented to demonstrate the mixed user equilibrium model. The results show that BEV drivers’ en-route recharging choice behaviors are significantly influenced by their battery safety margins, and under the equilibrium, the travel routes selected by some BEV drivers may not be optimal, but the total travel time may be more optimal.

Innovative Antriebe 2018

2018 ◽  
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Management System ◽  
Hybrid Electric Vehicles ◽  
Management Strategies ◽  
Battery Management System ◽  
Use Case ◽  
Battery Management ◽  
Hybrid Electric

Zukünftiges Mobilitätsverhalten Mobilität 2050 – Selfdriving-eCo-Hyperflyyer, Drahtesel, oder was? . . . . . . . . . . . . . . . . . . .1 K. C. Keller, Aveniture GmbH, Freinsheim Ökobilanzierung Einfluss von Zellbauform und Zellchemie auf die Ökobilanz von batterieelektrischen Fahrzeugen . . . . . . . . . .5 T. Semper, M. Clauß, IAV GmbH, Stollberg; A. Forell, IAV GmbH, Bad Cannstatt Anwendungsfallabhängige CO2 -Bilanzen elektrifizierter Fahrzeugantriebe –Use case driven CO2 footprint of electrified powertrains . . . . . . . . . . . . . . .17 O. Ludwig, J. Muth, M. Gernuks, H. Schröder, T. Löscheter Horst, Volkswagen AG, Wolfsburg Prädiktion der Lebensdauer von Traktionsbatteriesystemen für reale Nutzungsszenarien . . . .33 M. Ufert, Professur für Fahrzeugmechatronik, Technische Universität Dresden; A. Batzdorf, L. Morawietz, IAM GmbH, Dresden Predictive Energy Management Strategies for Hybrid Electric Vehicles: eHorizon for Battery Management System. . . . . 49 M. ...

Lithium Ion Battery Management Strategies for European Space Operations Centre Missions

2014 ◽  
Author(s):  
Thomas Ormston ◽  
Laurent Maleville ◽  
Viet Duc Tran ◽  
Luke Lucas ◽  
Kees Van Der Pols ◽  
...  
Keyword(s):  
Lithium Ion Battery ◽  
Management Strategies ◽  
Lithium Ion ◽  
Battery Management ◽  
Space Operations

Knowledge-based inventory management in production logistics: A multi-agent approach

2005 ◽  
Vol 219 (3) ◽  
pp. 299-307 ◽  
Author(s):  
C F Cheung ◽  
W M Wang ◽  
S K Kwok
Keyword(s):  
Inventory Management ◽  
Raw Materials ◽  
Management Strategies ◽  
Prototype System ◽  
Production Logistics ◽  
Knowledge Based ◽  
Inventory Management System ◽  
Material Requirement ◽  
Multi Agent ◽  
Dynamic Forecasting

With the rapidly changing market conditions, an accurate and highly dynamic inventory management model is much needed for making an enterprise more predictable to the global competition. However, traditional inventory management in production logistics is inadequate in managing inventories with high fluctuation in demand and value. To establish effective inventory management strategy, this paper presents a knowledge-based inventory management system for active inventory replenishment based on multi-agent dynamic forecasting and knowledge-based system technologies. The system dynamically forecasts the fluctuation of the demand and updates price of its raw materials. Hence, appropriate inventory management strategies are derived to respond and adapt to the rapid market changes and the material requirement. A prototype system has been built and successfully trial implemented in a manufacturing enterprise.

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