Development research about the power battery management system of pure electric vehicle

Sheng, Chuan

doi:10.1109/cecnet.2011.5769003

Cited by 10 publications

(4 citation statements)

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“…In order to obtain a more regular speed profile, a weighing process based on the distance and the difference between the segment slope and the mean slope (equation 3) is applied, assigning to each segment the theoretical best power that should be consumed along it-see equation 4. This consideration brings as result a greater power consumption assigned to upgrade segments and, on the other hand, downgrades are planned with less power cost.…”

Section: B Speed Profile Generationmentioning

confidence: 99%

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Optimal energy consumption algorithm based on speed reference generation for urban electric vehicles

Flores

Milanés

Pérez

et al. 2015

2015 IEEE Intelligent Vehicles Symposium (IV)

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International audiencePower consumption and battery life are two of the key aspect when it comes to improve electric transportation systems autonomy. This paper describes the design, development and implementation of a speed profile generation based on the calculation of the optimal energy consumption for electric Cybercar vehicles for each of the stretches that are covering. The proposed system considers a commuter daily route that is already known. It divides the pre-defined route into segments according to the road slope and stretch length, generating the proper speed reference. The developed system was tested on an experimental electric platform at Inria's facilities, showing a significant improvement in terms of energy consumption for a pre-defined route. I. INTRODUCTION Electric vehicles (EVs) are getting more and more attention because their contribution toward eco-friendly cities. Non-emission vehicles will definitely help to improve cit-izen's daily life, reducing dramatically both noise and pollution [1]. For this reason, some governments–i.e. Canada [2]–have carried out studies to figure out the emissions according to the kind of vehicle. Results showed that light duty gas vehicles are the biggest producer of CO 2 and the second greatest producer of N 2 O and methane, which makes them the main contributors towards gas emissions–because of their higher market penetration. In United States [3], the transportation sector consumes three-quarters of the total burned petroleum, which makes it the second largest carbon emitter in the country. Because of this, electric vehicles are an adequate solution to reduce greenhouse gas (GHG) emissions and pollution produced by road transport systems. On the other hand, EVs present serious limitations for their market deployment. Specifically, there are two unsolved challenges: 1) battery charge [4]: how long it takes to fully load when running off at driving; and 2) battery life [5]: how much energy will last when driving. Recent years have shown a lot of development on battery technologies– i.e. the mixed structures using supercapacitors [6] or fuel cells [7]. However, EVs autonomy remains considerably lower than gas-powered vehicles. This paper deals with this second challenge, proposing an intelligent modular algorithm that provides better performance in order to improve EVs autonomy. Specifically related with the solution to the EVs autonomy problem, there are two main ways for improving batter

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Section: B Speed Profile Generationmentioning

confidence: 99%

“…Specifically, there are two unsolved challenges: 1) battery charge [4]: how long it takes to fully load when running off at driving; and 2) battery life [5]: how much energy will last when driving. Recent years have shown a lot of development on battery technologiesi.e.…”

Section: Introductionmentioning

confidence: 99%

Optimal energy consumption algorithm based on speed reference generation for urban electric vehicles

Flores

Milanés

Pérez

et al. 2015

2015 IEEE Intelligent Vehicles Symposium (IV)

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“…A significant concern is how the vehicle, dependent on the battery pack, will perform in temperature extremes and the relationship to useable range must be examined [10]. The effect of humidity on the battery and electronics would need consideration [11]. Additionally, the change of air pressure, considering the elevation changes that are possible, and the potential affect on the battery needs some study [11].…”

Section: Environmental Concernsmentioning

confidence: 99%

“…The effect of humidity on the battery and electronics would need consideration [11]. Additionally, the change of air pressure, considering the elevation changes that are possible, and the potential affect on the battery needs some study [11].…”

Section: Environmental Concernsmentioning

confidence: 99%

Endurance Electric Vehicle Design and Development Considerations

Price¹

2012

JET

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This paper provides a preliminary battery assessment mechanism to address the hypothetical ECO-America EV Challenge. Several battery parameters are discussed in relation to pack needs, in addition to vehicle and environmental considerations. An evaluation method is provided, with a vision based on success and a metric for battery evaluation for the ECO-America Challenge. Five in-house testing procedures are also provided to ensure battery pack conformance and functionality. Finally, five scenarios are discussed that would cause the current evaluation method and metric to be revised.

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