A Life Cycle Assessment of lithium battery and hydrogen-FC powered electric bicycles: Searching for cleaner solutions to urban mobility

Mellino, Salvatore; Petrillo, Antonella; Cigolotti, Viviana; Autorino, Claudio; Jannelli, Elio; Ulgiati, Sérgio

doi:10.1016/j.ijhydene.2016.10.146

Cited by 48 publications

(24 citation statements)

References 18 publications

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“…The third phase is the impact assessment phase, which identifies the potential environmental effects. The fourth and last phase is the interpretation phase, in which information from the results are evaluated [56,57].…”

Section: Methodology and Resultsmentioning

confidence: 99%

Life Cycle Assessment (LCA) of Different Kinds of Concrete Containing Waste for Sustainable Construction

et al. 2018

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Concrete production causes significant environmental damage during its entire life cycle due to the large consumption of natural aggregate. The aim of this research was to use the Life Cycle Assessment (LCA) methodology to conduct a comparative analysis of four different concrete mixtures, i.e., construction and demolition waste (CDW), incinerator ashes, marble sludge, and blast furnace slag. The LCA study was implemented in the Campania Region of Italy. The main contribution of the study was that it proposed the use of "green" recycled aggregates in concrete production in order to assess the reduction of potential adverse impacts, from both environmental and energy perspectives. SimaPro © software was used to conduct the analysis. The main results of the research showed that the recycled aggregates that were analyzed were preferable to traditional concrete. In particular, the recycled aggregate that had the least adverse impact on the environment was blast furnace waste.

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Section: Methodology and Resultsmentioning

confidence: 99%

Life Cycle Assessment (LCA) of Different Kinds of Concrete Containing Waste for Sustainable Construction

et al. 2018

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“…The lowest prices were obtained for the hybrid storage implementations (battery-FC and SC-FC) and the highest for the FC implementation. * According to estimations and average values, 1 according to reference [69], 2 according to reference [25], 3 according to reference [17], for the tested pedelec, 4 according to reference [33], 5 according to reference [39], for the tested models, 6 according to reference [70], 7 according to reference [49], 8 according to reference [71], 9 according to reference [22], 10 according to reference [72], 11 according to reference [73], 12 according to reference [21], 13 according to reference [74], 14 according to reference [75], 15 according to reference [76], 16 according to reference [77], 17 according to reference [23], 18 according to reference [58], 19 according to reference [60], 20 according to reference [78], 21 according to reference [79], 22 according to reference [67]. Table 9.…”

Section: Life Cycle Assessment Of Hybrid Storage Implementations/solumentioning

confidence: 99%

Are Personal Electric Vehicles Sustainable? A Hybrid E-Bike Case Study

Machedon-Pisu

Borza

2019

Sustainability

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As the title suggests, the sustainability of personal electric vehicles is in question. In terms of life span, range, comfort, and safety, electric vehicles, such as e-cars and e-buses, are much better than personal electric vehicles, such as e-bikes. However, electric vehicles present greater costs and increased energy consumption. Also, the impact on environment, health, and fitness is more negative than that of personal electric vehicles. Since transportation vehicles can benefit from hybrid electric storage solutions, we address the following question: Is it possible to reach a compromise between sustainability and technology constraints by implementing a low-cost hybrid personal electric vehicle with improved life span and range that is also green? Our methodology consists of life cycle assessment and performance analyses tackling the facets of the sustainability challenges (economy, society, and environment) and limitations of the electric storage solutions (dependent on technology and application) presented herein. The hybrid electric storage system of the proposed hybrid e-bike is made of batteries, supercapacitors, and corresponding power electronics, allowing the optimal control of power flows between the system's components and application's actuators.Our hybrid e-bike costs less than a normal e-bike (half or less), does not depend on battery operation for short periods of time (a few seconds), has better autonomy than most personal electric vehicles (more than 60 km), has a greater life span (a few years more than a normal e-bike), has better energy efficiency (more than 90%), and is much cleaner due to the reduced number of batteries replaced per life time (one instead of two or three).

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“…The weight of each particle is 1/M. (II) Since the health degradation process of lithium batteries is a monotonic process in theory, the cumulative failure probability at time t can be expressed as follows according to the single threshold failure definition [21]:…”

Section: Vectors { }mentioning

confidence: 99%

Probabilistic Prediction Algorithm for Cycle Life of Energy Storage in Lithium Battery

Wang

Gao

Sun

2019

WEVJ

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Lithium batteries are widely used in energy storage power systems such as hydraulic, thermal, wind and solar power stations, as well as power tools, military equipment, aerospace and other fields. The traditional fusion prediction algorithm for the cycle life of energy storage in lithium batteries combines the correlation vector machine, particle filter and autoregressive model to predict the cycle life of lithium batteries, which are subjected to many uncertainties in the prediction process and to inaccurate prediction results. In this paper, a probabilistic prediction algorithm for the cycle life of energy storage in lithium batteries is proposed. The LS-SVR prediction model was trained by a Bayesian three-layer reasoning. In the iterative prediction phase, the Monte Carlo method was used to express and manage the uncertainty and its transitivity in a multistep prediction and to predict the future trend of a lithium battery's health status. Based on the given failure threshold, the probability distribution of the residual life was obtained by counting the number of particles passing through the threshold. The wavelet neural network was used to study the sample data of lithium batteries, and the mapping relationship between the probability distribution of the residual life of lithium batteries and the unknown values were established. According to this mapping relation and the probability distribution of the residual life of lithium batteries, the health data could be deduced and then iterated into the input of the wavelet neural network. In this way, the predicted degradation curve and the cycle life of lithium batteries could be obtained. The experimental results show that the proposed algorithm has good adaptability and high prediction efficiency and accuracy, with the mean error of 0.17 and only 1.38 seconds by average required for prediction.World Electric Vehicle Journal 2019, 10, 7 2 of 17 directly measured but needs to be estimated in advance to decide whether to replace the battery to avoid some unnecessary events. The performance of batteries can be divided into two categories: electrical performance and reliability. Battery life is one of the important indicators to measure the electrical performance of batteries. Charge-discharge cycles include a charge operation and a discharge operation. The number of charge-discharge cycles that a battery can carry out while maintaining a certain output capacity is called the cycle life (service life) of the battery. For energy storage batteries, it is generally believed that the life of the battery is terminated when the available capacity of the battery decreases to 70% of the initial level [4]. Battery life includes cycle life and calendar life, where the former refers to the number of cycles of the battery from a certain charging and discharging system to the end of life and the latter refers to the time required for the battery to be stored in a certain state until the end of life. There are many complex physical and chemical reactions in the charge and discha...

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A Life Cycle Assessment of lithium battery and hydrogen-FC powered electric bicycles: Searching for cleaner solutions to urban mobility

Cited by 48 publications

References 18 publications

Life Cycle Assessment (LCA) of Different Kinds of Concrete Containing Waste for Sustainable Construction

Life Cycle Assessment (LCA) of Different Kinds of Concrete Containing Waste for Sustainable Construction

Are Personal Electric Vehicles Sustainable? A Hybrid E-Bike Case Study

Probabilistic Prediction Algorithm for Cycle Life of Energy Storage in Lithium Battery

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