Vehicle Life Cycle Research Articles

Evaluation of the resource effectiveness of circular economy strategies through multilevel Statistical Entropy Analysis

In a circular economy (CE), materials, components and products should be kept at the highest level of functionality, while phenomena like dilution, mixing and contamination, often referred to as the loss of resources, should be avoided. One method that can assess the performance of systems to concentrate or avoid dilution of resources is Statistical Entropy Analysis (SEA). Up till now, the method has been applied on the substance level (elements and compounds) only, but showed its applicability to various scales and a variety of systems. Further development of the method allowed to consider information on the product, component and material levels, which makes the method applicable to different combinations of CE strategies, both destructive (e.g. recycling) and non-destructive (e.g. reuse). The method is demonstrated on a simplified vehicle life-cycle, which is modeled through four component groups and six materials. It shows that the method allows to evaluate different CE strategies and identify critical stages which lead to the most severe resource and functionality losses. Based on the method's results, it is possible to determine a perfect circularity reference level, representing a system state that preserves functionality and avoids resource losses. The introduction of a circularity reference level enables the establishment of a framework for resource effectiveness in which diluting and concentrating effects of activities (e.g. sorting) are quantified. The distance of a system to an ideal circular state determines the deviation from a resource-effective system that maintains the original product functionality over a maximum period of time, with minimal efforts.

Life Cycle Assessment of Electric Vehicle Batteries: An Overview of Recent Literature

In electric and hybrid vehicles Life Cycle Assessments (LCAs), batteries play a central role and are in the spotlight of scientific community and public opinion. Automotive batteries constitute, together with the powertrain, the main differences between electric vehicles and internal combustion engine vehicles. For this reason, many decision makers and researchers wondered whether energy and environmental impacts from batteries production, can exceed the benefits generated during the vehicle’s use phase. In this framework, the purpose of the present literature review is to understand how large and variable the main impacts are due to automotive batteries’ life cycle, with particular attention to climate change impacts, and to support researchers with some methodological suggestions in the field of automotive batteries’ LCA. The results show that there is high variability in environmental impact assessment; CO2eq emissions per kWh of battery capacity range from 50 to 313 g CO2eq/kWh. Nevertheless, either using the lower or upper bounds of this range, electric vehicles result less carbon-intensive in their life cycle than corresponding diesel or petrol vehicles.

Battery life estimation based on cloud data for electric vehicles

To evaluate the safety and life-cycle of electric vehicles (EVs), automobile companies usually retain the driving data of EVs on the cloud for monitoring and management. The recording period of the cloud data is generally as long as 10–30 s at present, so the dynamic driving condition of EVs is hard to be revealed with the cloud data. But the charging data are stable, which makes it possible to estimate the battery life based on the charging cloud data. Battery life estimation includes capacity estimation and internal resistance estimation. In this paper, the capacity is directly estimated by the ampere hour integral method. The estimation results are modified based on the temperature data and optimized by the Kalman filter (KF). We further propose the Fuzzy logic (FL) to control the observation noise which effectively improves the accuracy of the estimation results. Then, the battery life is predicted by the Arrhenius empirical model. The sudden changes of voltage and current in the charging data are used for estimating the internal resistance. The internal resistance prediction is achieved using a similar process to the capacity prediction. The sampling test shows that the errors of the battery life estimation method are less than 4%.

Predictive Analysis of New Energy Vehicle Life Cycle Based On Logistic Model

This article uses (new energy vehicle or electric vehicle or hybrid vehicle or fuel cell vehicle or hydrogen energy powered vehicle or solar vehicle) as the search key, Based on the new energy vehicle invention patent data retrieved in the SooPAT patent search engine, The logistic model is used to analyze the life cycle of China’s new energy vehicle technology, to predict and analyze the technology, and to summarize the development stage of China’s new energy vehicle technology. Research shows that China’s new energy vehicle technology has begun to sprout from the early 1990s. After a 23-year technology introduction period, it entered the growth stage in 2014, entered a mature period in 2020, and is expected to enter a recession in 2026. Finally reveal the current status and future development trends of technology in this field in China.

Based on the Patent Index Method and S Curve Method Prediction Analysis of Pure Electric Vehicle Life Cycle

In order to grasp the direction of pure electric vehicle technology innovation in strategic macro, this paper retrieves the domestic patents in the field related to pure electric vehicles, using the patent index method and S-curve method to analyze the life cycle of pure electric vehicle technology. It is clear that the pure electric vehicle technology in China is in the mature stage of the technology life cycle, In view of the development stage and development trend of pure electric vehicle technology in China, this paper provides patent strategies for related enterprises from the perspective of patent strategy. The combination of patent indicator method and s-curve method can predict the technology life cycle more accurately, providing a feasible analytical method for the identification and prediction of the patent technology life cycle.

Life cycle assessment of fuel cell, electric and internal combustion engine vehicles under different fuel scenarios and driving mileages in China

As the result of the growing problems of energy shortage and environmental pollution, the world needs more energy-saving and low-emissions vehicles. Although most future vehicles claim to have good performance, their real effects on sustainability in the life cycle under complex scenarios still need careful evaluation. In this study, a comprehensive and state-of-the-art life cycle assessment of the fuel cell vehicle, electric vehicle and internal combustion engine vehicle in China is conducted to compare their sustainability under different hydrogen production methods and driving mileages. The results show that primary energy consumption and greenhouse gas emissions of electric vehicles in the vehicle life cycle is significantly higher than that of the other two vehicles caused by the high energy consumption and emissions of battery production. In the total life cycle, fuel cell vehicles using hydrogen from electrolysis by abandoned hydropower and coke oven gas have the best performance among all scenarios when the driving mileage reaches around 75,000 km, and their advantage will become more obvious with increasing the driving mileage. In summary, it is necessary to select proper vehicle and fuel scenario based on the driving mileage to achieve good sustainability impact.

A probabilistic fleet analysis for energy consumption, life cycle cost and greenhouse gas emissions modelling of bus technologies

Introducing alternative bus fleet technologies requires investigation into life cycle impacts, risks and benefits. Previous modelling approaches comparatively assess individual vehicle energy demands and life cycle impacts, assuming alternative technologies can fulfil identical life cycle functions to a diesel baseline. This assumption neglects the influence that service frequency, capacity and range limitations have on daily operations and fleet and infrastructure sizing. The goal of this study was to develop a framework to investigate bus fleet operation in terms of the risk and uncertainty of an alternative drivetrain technology’s ability to mitigate life cycle costs and greenhouse gas emissions. Probabilistic simulation enabled risk and uncertainty quantification of diesel, micro-hybrid, mild-hybrid and battery-electric fleet scenarios for a UK case study. The fleet analysis approach revealed decreased potential to reduce life cycle costs and greenhouse gas emissions from battery-electric buses. Compared to a baseline single-deck diesel fleet at low risk levels, the micro-hybrid double-deck fleet delivers the largest life cycle cost savings (18.7%). The largest life cycle greenhouse gas emissions savings come from the mild-hybrid lithium-titanate single-deck fleet (20.8%). Double-deck micro and mild hybrid fleets are the most effective at saving both life cycle costs and greenhouse gas emissions. The modelling approach adds a novel probabilistic capability for making comparative fleet-wide assertions, supporting the decision-making process for implementing new sustainable fleet technologies.

Eco-efficiency of the differential ratio change in a heavy-duty vehicle and implications for the automotive industry

The transport sector is seen as the main responsible for greenhouse gas emissions, accounting for approximately 33% of global emissions. Faced with this environmental concern, the automotive sector has sought to incorporate sustainability into the life cycle of vehicles, via for instance, eco-efficiency approaches. The aim of this paper was to demonstrate the environmental and economic effects of the change in the differential ratio in a heavy-duty vehicle. Thus, a detailed case study was carried out. From an environmental perspective, a Life Cycle Assessment was conducted to quantify the potential impacts considering the impact categories of (i) resource consumption, human health with (ii) carcinogenic and (iii) effects, and (iv) global warming potential. Life Cycle Assessment results indicated an average of 6.50% impact reduction for each category analyzed, due to the change in the differential ratio. Moreover, from an economic perspective, it was observed a reduction of 5000 liters/year of diesel consumption for the studied truck, which was equivalent to BRL 15,000.

Методологічні основи оптимізації рішень в проектах створення автомобілів оперативних служб

The article discusses the problems of finding the optimal concept for creation’s projects of new generation operational cars taking into account the multipurpose nature of their functioning. The analysis of the purpose of operational vehicles, the generalization of the functions of operational vehicles is carried out, the elements are determined by which the requirements for them are formed, the general requirements for operational vehicles and a performance criterion for an operational vehicle are proposed, and the compliance of existing operational vehicles with the established requirements. A new approach to assessing the operational characteristics of an operational vehicle as an integrated system is proposed, and the requirements are determined, the compliance with which will ensure the highest efficiency of an operational vehicle. Such approach is associated with solving a complex of problems throughout the entire life cycle of operational vehicles as a polysyllabic optimization problem. The solution to this problem should mainly be based on the development of theoretical and methodological foundations and new information technologies for determining and ensuring the efficiency of operational vehicles during their operation in order to rationally substantiate design parameters according to the corresponding efficiency criterion associated with the temporal characteristics of their functioning in the environment of intended use. The creation (selection) of the base chassis is one of the most critical stages of the design and construction processes of operational vehicles. The chassis created (selected) for such vehicle must have such parameters (structural, operational, economic) that minimize the target function of the fire truck, at given costs for the production and operation of equipment. Concrete measures are proposed for the creation (selection) of basic chassis of operational vehicles.

Reliability Assessment Based on GO Method of Metro Traction System

In order to improve the reliability of the metro traction system (MTS), the whole life cycle of metro vehicles can be operated safely and reliably. A reliability assessment method based on the GO method of the MTS is proposed. In this paper, the reliability assessment is completed without operation service failure of the metro vehicle. The maintainability and shutdown correlation of many electrical components in the MTS are considered. An accurate algorithm with shared signals is used. Then the quantitative and qualitative reliability assessment of the system is achieved with the goal of traction system providing traction for the vehicle. The evaluation identifies the weak links of the system. Comparing the completely independent quantitative calculation result of each component with the accurate quantitative calculation results, it is found that the complex correlation in the repairable system has an important effect on the reliability of the system. A comparative analysis is performed on the calculating results of the GO method and fault tree analysis (FTA) method. The results demonstrate that the reliability analysis of the MTS by the GO method is feasible and reasonable. The principle of the method is simple and the logic is clear. It can not only objectively reflect the working process of the MTS, but also fully characterize the complex correlation with shut down fault in the MTS. The qualitative assessment results of the system show that the cut set probability of the pantograph is the highest, which should be the focus of the MTS.

A Novel Blockchain-Based Framework for Vehicle Life Cycle Tracking: An End-to-End Solution

Transactions related to vehicles include manufacturing, buying, selling, paying insurance(takaful), obtaining regular inspection, leasing a vehicle from banks, getting in an accident, engaging in a traffic violation, calculating price predictions and renting a vehicle. Many people perform transactions related to vehicles in their daily life; transportation authorities also perform vehicle transactions as part of managing vehicle fleets. But tracking these transactions is a challenging task. There are countrywide solutions that uses centralized systems. However, these solutions have problems with trust management, transparency, and access control. Therefore, we believe there is still room for integrated automation of various vehicle-related transactions. In this paper, we present a blockchain-based framework for vehicle tracking that incorporates the mentioned features. Moreover, blockchain is customized to enable usage control for additional transactions, such as inspection, renting and islamic insurance. The usage control model is integrated with IoT devices to continuously monitor the vehicles for certain conditions and remotely revoke access if needed. The complete transaction set is recorded over an immutable ledger that provides trust, transparency and a complete history of record. In this paper, we also presents a prototype implementation of a permissioned blockchain, which will be made available under the GNUv3 General Public License. Performance analysis is performed on the newly proposed framework implementation over the permissioned blockchain to measure its adoption and suitability.

Inventory and life cycle assessment of an Italian automotive painting process

In the current context of the European Environmental legislation and standards, the automotive sector is expected to continuously improve the vehicles life cycle with solutions able to minimise emissions of greenhouse gases and other negative effects on the environment and on human health. The vehicle painting process has been identified to be responsible of significant potential impacts, but recent primary inventory data and impact results are currently scarcely available in the literature. The novelty of this paper is the provision of a comprehensive life cycle inventory and life cycle assessment (LCA) of a painting process, with reference to a large and highly automated plant located in Turin (Italy). To achieve these goals, the highly recognised methodology of LCA has been followed, as indicated in ISO 14040-44. A detailed inventory is disclosed (both as input/output table and ILCD file) for the four main phases of the painting process (electrodeposition, primer application, top coat application and final drying and revision). Impact results on the categories of climate change, acidification, terrestrial eutrophication and photochemical ozone creation potential are quantified as well. These latter show that the major hot points are the high-energy consumption (specifically, the integrated provision of technological heating and chilled water is responsible of almost half of the total emissions of greenhouse gases), the direct emission of volatile organic compounds into air (for a total of 7.44 kg/car) and the waste production and treatment [giving a significant contribution to the impact categories of ozone depletion (99%), freshwater eutrophication (66%) and freshwater ecotoxicity potential (60%)]. This study contributes to increase the pool of publicly available life cycle data for specific applications in the automotive sector. In addition, the easy replicability and adaptation of the provided inventory is expected to boost enterprises to increase their overall sustainability. Finally, this study provides data and tools for the development of further research in alternative painting technologies.

A Comparative Study of Carbon Footprint Lifecycle of Diesel Engine Automobile and Electric Vehicles

A Comparative Study of Carbon Footprint Lifecycle of Diesel Engine Automobile and Electric Vehicles

Towards Holistic Energy-Efficient Vehicle Product System Design: The Case for a Penalized Continuous End-of-Life Model in the Life Cycle Energy Optimisation Methodology

AbstractThe Life Cycle Energy Optimisation (LCEO) methodology aims at finding a design solution that uses a minimum amount of cumulative energy demand over the different phases of the vehicle's life cycle, while complying with a set of functional constraints. This effectively balances trade-offs, and therewith avoids sub-optimal shifting between the energy demand for the cradle-to-production of materials, operation of the vehicle, and end-of-life phases. The present work describes the extension of the LCEO methodology to perform holistic product system optimisation. The constrained design of an automotive component and the design of a subset of the processes which are applied to it during its life cycle are simultaneously optimised to achieve a minimal product system life cycle energy. A subset of the processes of the end-of-life phase of a vehicle's roof are modeled through a continuous formulation. The roof is modeled as a sandwich structure with its design variables being the material compositions and the thicknesses of the different layers. The results show the applicability of the LCEO methodology to product system design and the use of penalization to ensure solution feasibility.

Representing vehicle-technological opportunities in integrated energy modeling

Light-duty vehicles (LDVs) are responsible for more than one tenth of global energy use and CO2 emissions and are therefore an important focus in pollution mitigation efforts. Integrated energy models (IEMs) are frequently used to explore cost-optimal climate change mitigation measures for energy supply and demand sectors, such as LDVs. Options include fuel and powertrain switching through efficiency standards, taxation, and technology mandates. This review provides an overview on how LDVs are modeled in 14 popular IEMs. We find that the representation of mitigation options can be enhanced by linking emissions and physical outputs from industry, agriculture, and energy conversion directly to the vehicle life cycle and by more carefully reflecting important factors that influence LDV life cycle emissions. This would allow for a more complete internalization of emissions in the technology mix optimization procedure of IEMs. The results highlight a range of mitigation options currently not considered in most integrated models, such as reducing embodied emissions in infrastructure and vehicle production, reducing methane leakage, or switching to less carbon intensive crude oil grades.

Environment for Planning Unmanned Aerial Vehicles Operations

Planning and executing missions in terms of trajectory generation are challenging problems in the operational phase of unmanned aerial vehicles (UAVs) lifecycle. The growing adoption of UAVs in several civil applications requires the definition of precise procedures and tools to safely manage UAV missions that may involve flight over populated areas. The paper aims at providing a contribution toward the definition of a reliable environment, called FLIP (flight planner) for route planning and risk evaluation in the framework of mini- and micro-UAV missions over populated areas. The environment represents a decision support system (DSS) for UAV operators and other decision makers, like airports authorities and aviation agencies. A new ICT tool integrating an innovative procedure for evaluating the risk related to the use of UAV over populated areas is proposed.

A life-cycle assessment of battery electric and internal combustion engine vehicles: A case in Hebei Province, China

Vehicle electrification has been rapidly promoted to aid the conventional energy shortage and reduce environmental pressures for light-duty passenger vehicles (LDPVs). Battery electric vehicles (BEVs) are well positioned in the electric vehicle market. This article presents a cradle-to-grave assessment of energy consumption, CO2 emissions and emissions of VOC, CO, NOx, primary PM2.5 and PM10 for current (2015) and future (2020 and 2030) LDPVs in Hebei Province, China. The analysis addressed both the fuel life cycle and vehicle life cycle for conventional gasoline and battery electric LDPVs. A scenario analysis was carried out to evaluate the reduction potentials of different future policies. The results showed that the promotion of BEVs could effectively mitigate per-kilometer petroleum use by 98% and fossil fuel use by 25–50% relative to gasoline LDPVs. BEVs hold obvious advantages in CO2, VOCs, CO, NOx and PM2.5 emissions reduction, while the PM10 emissions of BEVs are higher than those of conventional internal combustion engine vehicles, mainly due to the high emission in the upstream industry process in electricity generation. The scenario analysis showed that the emissions of VOCs, CO, NOx, PM2.5 and PM10 will decrease by 56%, 70%, 27%, 24% and 17%, respectively, with the China Ⅵ oil standard coming into force in 2030 instead of 2020. The results stress that more stringent emission controls, higher BEV penetration, and cleaner electricity should be jointly applied to ensure a successful electrification future in China.

Researching logistic processes in motorization

The purpose of the article is to identify and analyze various logistic processes that may occur in the life cycle of an automobile vehicle and attempt to assign them to specific groups of activities of a similar nature. Processes occurring in road motorization, especially those related to the use of passenger cars, which can be identified as logistic processes are described. The research was divided into four stages, according to the life cycle of vehicles. The links existing in the supply chain between individual logistics subsystems on each are underlined from these stages. The result of the research work is the determination of a considerable degree of complexity of logistic activities in this area and their mutual dependence as well as a large variety of issues, which proves the interdisciplinary nature of logistics. A comprehensive look at this issue allows to understand the consequences of some decisions taken, for example, at the design stage for the remaining stages, including endof- life processes and, above all, requirements from the point of view of sustainable development. The conclusions that can be drawn from the conducted analyzes allow to state that it is justified to search for and identify all activities that may be logistic in order to plan and control the mutual influence of some activities (decisions) on other, sometimes very remote in time, in strategic dimension.

Carbon Footprint and Water Footprint of Electric Vehicles and Batteries Charging in View of Various Sources of Power Supply in the Czech Republic

In the light of recent developments regarding electric vehicle market share, we assess the carbon footprint and water footprint of electric vehicles and provide a comparative analysis of energy use from the grid to charge electric vehicle batteries in the Czech Republic. The analysis builds on the electricity generation forecast for the Czech Republic for 2015–2050. The impact of different sources of electricity supply on carbon and water footprints were analyzed based on electricity generation by source for the period. Within the Life Cycle Assessment (LCA), the carbon footprint was calculated using the Intergovernmental Panel on Climate Change (IPCC) method, while the water footprint was determined by the Water Scarcity method. The computational LCA model was provided by the SimaPro v. 8.5 package with the Ecoinvent v. 3 database. The functional unit of study was running an electric vehicle over 100 km. The system boundary covered an electric vehicle life cycle from cradle to grave. For the analysis, we chose a vehicle powered by a lithium-ion battery with assumed consumption 19.9 kWh/100 km. The results show that electricity generated to charge electric vehicle batteries is the main determinant of carbon and water footprints related to electric vehicles in the Czech Republic. Another important factor is passenger car production. Nuclear power is the main determinant of the water footprint for the current and future electric vehicle charging, while, currently, lignite and hard coal are the main determinants of carbon footprint.

Effect of hygrothermal aging on the quasi-static behaviour of CFRP joints varying the overlap length

Adhesively bonded joints with composite substrates are crucial for the manufacture of lightweight structural components for the automotive industry. However, the safety of the vehicles must still be ensured after hygrothermal aging of both composite substrates and adhesive, as adverse conditions such as moisture and temperature will be a constant during a vehicle lifecycle. This work studies the influence of hygrothermal aging and temperature on the quasi-static behaviour of adhesive joints made with unidirectional composite substrates and a crash resistant adhesive using different overlap lengths. A complementary numerical simulation was performed to model both the water uptake processes and the failure process of moisture affected materials. Both the simulation and the experimental data showed increased susceptibility to delamination failure induced by water absorption in the composite and changes in the adhesive properties.