Optimal Battery-Structure Composites for Electric Vehicles

2016 ◽  
Author(s):  
Jun Ma ◽  
Christopher Rahn ◽  
Mary Frecker
Keyword(s):  
Electric Vehicles ◽  
Research Area ◽  
Original Design ◽  
Vehicle Weight ◽  
Vehicle Mass ◽  
Energy Constraints ◽  
Driving Range ◽  
Light Weighting ◽  
The Cost ◽  
Mechanical Rigidity

Light-weighting is a key research area for reducing the cost of electric vehicles (EVs). In this paper, multifunctional battery-structure composites, PowerPanels, are introduced, modeled and analyzed. To demonstrate the advantages of PowerPanels in EV applications, the Tesla Model S85 frame is redesigned. Component masses and bending stiffnesses are estimated for Tesla’s original design. The optimal PowerPanel design minimizes the vehicle weight under geometric, mechanical, and energy constraints. Including vehicle mass compounding effect, the redesigned vehicle is 350 kg lighter and its chassis is 0.418 m3 smaller, with the same mechanical rigidity and driving range.

scholarly journals MODELING AND ANALYSIS OF AN ELECTRIC VEHICLE USING PAMVEC

2018 ◽  
Vol 17 (2) ◽  
pp. 37
Author(s):  
S. C. A. de Almeida ◽  
F. L. A. Vieira
Keyword(s):  
Energy Consumption ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Specific Energy ◽  
Fossil Fuel ◽  
Modeling And Analysis ◽  
Acceptable Range ◽  
Battery Packs ◽  
Driving Range ◽  
The Cost

Electric vehicles are considered a key technology to reduce fossil fuel consumption, emissions and energy consumption. However, Electric Vehicles require larger battery packs to reach acceptable range levels. The development of new batteries with higher specific energy could reduce the mass and the cost of Electric Vehicles and increase their driving range. This work analyzes the influence of battery specific energy on battery pack mass, energy consumption and the cost per kilometer of a Tesla Model S Electric Vehicle. The energy consumption and the cost per kilometer calculated were 0.221 kWh/km (22.1 kWh/100 km) and 0.024 US$/km respectively.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

Energy After COVID

2020 ◽  
Vol 119 (820) ◽  
pp. 317-322
Author(s):  
Michael T. Klare
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Fossil Fuels ◽  
Fossil Fuel ◽  
White Collar ◽  
Peak Oil ◽  
Business Travel ◽  
Reduce Energy Consumption ◽  
The Cost ◽  
Energy Companies

By transforming patterns of travel and work around the world, the COVID-19 pandemic is accelerating the transition to renewable energy and the decline of fossil fuels. Lockdowns brought car commuting and plane travel to a near halt, and the mass experiment in which white-collar employees have been working from home may permanently reduce energy consumption for business travel. Renewable energy and electric vehicles were already gaining market share before the pandemic. Under pressure from investors, major energy companies have started writing off fossil fuel reserves as stranded assets that are no longer worth the cost of extracting. These shifts may indicate that “peak oil demand” has arrived earlier than expected.

scholarly journals Privileging Electric Vehicles as an Element of Promoting Sustainable Urban Mobility—Effects on the Local Transport System in a Large Metropolis in Poland

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3838
Author(s):  
Marta Borowska-Stefańska ◽  
Michał Kowalski ◽  
Paulina Kurzyk ◽  
Miroslava Mikušová ◽  
Szymon Wiśniewski
Keyword(s):  
Transport System ◽  
Electric Vehicles ◽  
Traffic Management ◽  
Negative Impact ◽  
Software Tool ◽  
Research Area ◽  
Shopping Centre ◽  
Local Transport ◽  
Sustainable Urban Mobility ◽  
The Impact

The main purpose of this article was to determine the impact on the equilibrium of the local transport system from privileging EVs by permitting them to use bus lanes. The study used two sets of data: information on infrastructure and traffic management; and information on the recorded road network loads and traffic volumes generated by a given shopping centre—the E. Leclerc shopping centre (an important traffic generator within the city of Łódź, Poland). These sets were then used to develop a microsimulation traffic model for the shopping centre and the associated effects on the localised transport system. The model was constructed by means of the PTV Vissim software tool. An initial simulation was conducted that formed a basis for subsequent scenarios (in total, 17 simulations were performed). On the basis of the conducted analyses, it was established that—for the researched part of the transport system—privileging the still rather uncommon battery electric vehicles (BEVs) engendered a marginal deterioration of traffic conditions. At the same time, allowing BEVs to use bus lanes within the chosen research area had no negative impact on bus journey times.

Progress and Prospects for the Development of Computer-Generated Actors for Military Simulation: Part 1-Introduction and Background

2003 ◽  
Vol 12 (3) ◽  
pp. 311-325 ◽  
Author(s):  
Martin R. Stytz ◽  
Sheila B. Banks
Keyword(s):  
Research Area ◽  
Background Information ◽  
Life Cycle Costs ◽  
Material Management ◽  
Reasoning System ◽  
Force Structure ◽  
The Cost ◽  
Future Work ◽  
Level Training ◽  
Made In

The development of computer-generated synthetic environments, also calleddistributed virtual environments, for military simulation relies heavily upon computer-generated actors (CGAs) to provide accurate behaviors at reasonable cost so that the synthetic environments are useful, affordable, complex, and realistic. Unfortunately, the pace of synthetic environment development and the level of desired CGA performance continue to rise at a much faster rate than CGA capability improvements. This insatiable demand for realism in CGAs for synthetic environments arises from the growing understanding of the significant role that modeling and simulation can play in a variety of venues. These uses include training, analysis, procurement decisions, mission rehearsal, doctrine development, force-level and task-level training, information assurance, cyberwarfare, force structure analysis, sustainability analysis, life cycle costs analysis, material management, infrastructure analysis, and many others. In these and other uses of military synthetic environments, computer-generated actors play a central role because they have the potential to increase the realism of the environment while also reducing the cost of operating the environment. The progress made in addressing the technical challenges that must be overcome to realize effective and realistic CGAs for military simulation environments and the technical areas that should be the focus of future work are the subject of this series of papers, which survey the technologies and progress made in the construction and use of CGAs. In this, the first installment in the series of three papers, we introduce the topic of computer-generated actors and issues related to their performance and fidelity and other background information for this research area as related to military simulation. We also discuss CGA reasoning system techniques and architectures.

scholarly journals Current Trends for State-of-Charge (SoC) Estimation in Lithium-Ion Battery Electric Vehicles

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3284
Author(s):  
Ingvild B. Espedal ◽  
Asanthi Jinasena ◽  
Odne S. Burheim ◽  
Jacob J. Lamb
Keyword(s):  
Electric Vehicles ◽  
Lithium Ion ◽  
Research Area ◽  
State Of Charge ◽  
Stable Operation ◽  
Battery Management ◽  
Soc Estimation ◽  
Current Trends ◽  
Battery Management Systems ◽  
Active Research

Energy storage systems (ESSs) are critically important for the future of electric vehicles. Despite this, the safety and management of ESSs require improvement. Battery management systems (BMSs) are vital components in ESS systems for Lithium-ion batteries (LIBs). One parameter that is included in the BMS is the state-of-charge (SoC) of the battery. SoC has become an active research area in recent years for battery electric vehicle (BEV) LIBs, yet there are some challenges: the LIB configuration is nonlinear, making it hard to model correctly; it is difficult to assess internal environments of a LIB (and this can be different in laboratory conditions compared to real-world conditions); and these discrepancies can lead to raising the instability of the LIB. Therefore, further advancement is required in order to have higher accuracy in SoC estimation in BEV LIBs. SoC estimation is a key BMS feature, and precise modeling and state estimation will improve stable operation. This review discusses current methods use in BEV LIB SoC modelling and estimation. The review culminates in a brief discussion of challenges in BEV LIB SoC prediction analysis.

Transfer Function Prediction of a Lithium Iron Phosphate Battery with Nature-Inspired Approach

2015 ◽  
Vol 1115 ◽  
pp. 531-534
Author(s):  
Siti Fauziah Toha
Keyword(s):  
Transfer Function ◽  
Electric Vehicles ◽  
Cross Correlation ◽  
Lithium Iron Phosphate ◽  
Iron Phosphate ◽  
Battery Lifetime ◽  
Battery Model ◽  
Full Capacity ◽  
Driving Range ◽  
Optimisation Technique

It is well known that the main constraint of electric vehicles (EVs) is the capabilities to supply efficient energy for driving-range that is comparable to petrol fueled vehicles. Moreover, a large number of batteries needed for EV contribute to heavy weight, poor durability and pricy total cost. In view of that, the need to prolong the battery lifetime, and use its full capacity, is of utmost importance. Therefore, an accurate battery model is a challenging first step to the overall problem soving chain. This paper presents a transfer function model prediction with nature-inspired approach for a Lithium iron phosphate battery. An Ant Colony Optimisation technique is used in search for accurate model with robust capability to adapt with different input current based on the New European Driving Cycle (NEDC) range. The model is further validated with autocorrelation and cross-correlation test and it is proven to give an error tolerance between the 95% confidence limit.

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