Forecasting the state of health of electric vehicle batteries to evaluate the viability of car sharing practices

Car sharing practices are introducing electric vehicles into their fleet. However, literature suggests that at this point shared electric vehicle systems are failing to reach satisfactory commercial viability. Potential reason for this is the effect of higher vehicle usage which is characteristic for car sharing, and the implication on the battery state of health. In this paper, we forecast state of health for two identical electric vehicles shared by two different car sharing practices. For this purpose, we use real life transaction data from charging stations and different electric vehicles’ sensors. The results indicate that insight into users’ driving and charging behaviour can provide valuable point of reference for car sharing system designers. In particular, the forecasting results show that the moment when electric vehicle battery reaches its theoretical end of life can differ in as much as ¼ of time when vehicles are shared under different conditions

Evidence and Ideology in Macroeconomics: The Case of Investment Cycles

The paper reports the principal findings of a long term research project on the description and explanation of business cycles. The research strongly confirmed the older view that business cycles have large systematic components that take the form of investment cycles. These quasi-periodic movements can be represented as low order, stochastic, dynamic processes with complex eigenvalues. Specifically, there is a fixed investment cycle of about 8 years and an inventory cycle of about 4 years. Maximum entropy spectral analysis was employed for the description of the cycles and continuous time econometrics for the explanatory models. The central explanatory mechanism is the second order accelerator, which incorporates adjustment costs both in relation to the capital stock and the rate of investment. By means of parametric resonance it was possible to show, both theoretically and empirically how cycles aggregate from the micro to the macro level. The same mathematical tool was also used to explain the international convergence of cycles. I argue that the theory of investment cycles was abandoned for ideological, not for evidential reasons. Methodological issues are also discussed

Evidence and Ideology in Macroeconomics: The Case of Investment Cycles

The paper reports the principal findings of a long term research project on the description and explanation of business cycles. The research strongly confirmed the older view that business cycles have large systematic components that take the form of investment cycles. These quasi-periodic movements can be represented as low order, stochastic, dynamic processes with complex eigenvalues. Specifically, there is a fixed investment cycle of about 8 years and an inventory cycle of about 4 years. Maximum entropy spectral analysis was employed for the description of the cycles and continuous time econometrics for the explanatory models. The central explanatory mechanism is the second order accelerator, which incorporates adjustment costs both in relation to the capital stock and the rate of investment. By means of parametric resonance it was possible to show, both theoretically and empirically how cycles aggregate from the micro to the macro level. The same mathematical tool was also used to explain the international convergence of cycles. I argue that the theory of investment cycles was abandoned for ideological, not for evidential reasons. Methodological issues are also discussed.business cycle; continuous time econometrics; investment cycle; inventory cycle; maximum entropy spectral analysis; parametric resonance

Rhythmic dynamics and synchronization via dimensionality reduction : application to human gait

Reliable characterization of locomotor dynamics of human walking is vital to understanding the neuromuscular control of human locomotion and disease diagnosis. However, the inherent oscillation and ubiquity of noise in such non-strictly periodic signals pose great challenges to current methodologies. To this end, we exploit the state-of-the-art technology in pattern recognition and, specifically, dimensionality reduction techniques, and propose to reconstruct and characterize the dynamics accurately on the cycle scale of the signal. This is achieved by deriving a low-dimensional representation of the cycles through global optimization, which effectively preserves the topology of the cycles that are embedded in a high-dimensional Euclidian space. Our approach demonstrates a clear advantage in capturing the intrinsic dynamics and probing the subtle synchronization patterns from uni/bivariate oscillatory signals over traditional methods. Application to human gait data for healthy subjects and diabetics reveals a significant difference in the dynamics of ankle movements and ankle-knee coordination, but not in knee movements. These results indicate that the impaired sensory feedback from the feet due to diabetes does not influence the knee movement in general, and that normal human walking is not critically dependent on the feedback from the peripheral nervous system

Crash/Near-Crash: Impact of Secondary Tasks and Real-Time Detection of Distracted Driving

The main goal of this dissertation is to investigate the problem of distracted driving from two different perspectives. First, the identification of possible sources of distraction and their associated crash/near-crash risk. That can assist government officials toward more informed decision-making process, allowing for optimized allocation of available resources to reduce roadway crashes and improve traffic safety. Second, actively counteracting the distracted driving phenomenon by quantitative evaluation of eye glance patterns. This dissertation research consists of two different parts. The first part provides an in-depth analysis for the increased crash/near-crash risk associated with different secondary task activities using the largest real-world naturalistic driving dataset (SHRP2 Naturalistic Driving Study). Several statistical and data mining techniques are developed to analyze the distracted driving and crash risk. More specifically, two different models were employed to quantify the increased risk associated with each secondary task: a baseline-category logit model, and a rule mining association model. The baseline-category logit model identified the increased risk in terms of odds ratios, while the A-priori association algorithm detected the associated risks in terms of rules. Each rule was then evaluated based on the lift index. The two models succeeded in ranking all the secondary task activities according to the associated increased crash/near-crash risk efficiently. To actively counteract to the distracted driving phenomenon, a new approach was developed to analyze eye glance patterns and quantify distracted driving behavior under safety and non-Safety Critical Events (SCEs). This approach is then applied to the Naturalistic Engagement in Secondary Tasks (NEST) dataset to investigate how drivers allocate their attention while driving, especially while distracted. The analysis revealed that distracted driving behavior can be well characterized using two new distraction risk indicators. Additional statistical analyses showed that the two indicators increase significantly for SCE compared to normal driving events. Consequently, an artificial neural network (ANN) model was developed to test the SCEs predictability power when accounting for the two new indicators. The ANN model was able to predict the SCEs with an overall accuracy of 96.1%. This outcome can help build reliable algorithms for in-vehicle driving assistance systems to alert drivers before SCEs

Moving forward in circles: challenges and opportunities in modelling population cycles

Population cycling is a widespread phenomenon, observed across a multitude of taxa in both laboratory and natural conditions. Historically, the theory associated with population cycles was tightly linked to pairwise consumer–resource interactions and studied via deterministic models, but current empirical and theoretical research reveals a much richer basis for ecological cycles. Stochasticity and seasonality can modulate or create cyclic behaviour in non-intuitive ways, the high-dimensionality in ecological systems can profoundly influence cycling, and so can demographic structure and eco-evolutionary dynamics. An inclusive theory for population cycles, ranging from ecosystem-level to demographic modelling, grounded in observational or experimental data, is therefore necessary to better understand observed cyclical patterns. In turn, by gaining better insight into the drivers of population cycles, we can begin to understand the causes of cycle gain and loss, how biodiversity interacts with population cycling, and how to effectively manage wildly fluctuating populations, all of which are growing domains of ecological research

Electrified road transport through plug-in hybrid powertrains: Compliance by simulation of CO2 specific emission targets with real driving cycles

Worldwide targets on specific CO2 emissions (g/km) seem to make the use of internal combustion engines (ICE) prohibitive when adopting conventional driving cycles concerning road transport. This research comes therefore from the necessity of an accurate analysis of the real driving habits in order to evaluate whether its implementation on an alternative powertrain, suitable to differentiate urban (local zero emissions) and extra-urban travels (highest performances of ICEs, even better than electric motors when contemplating the entire energy chain), can guarantee the compliance with specific CO2 emissions reduction legislation; this last has been introduced with the aim of containing or even erasing global emissions from the transport sector in next years. After an overview of all the main available technological alternatives, as regards powertrains, the Plug-in Hybrid (PHEV) solution has been analysed. An experimental driving cycle is proposed by combining representative cycles obtained from a previous study, based on data provided by FCA, now Stellantis, where a clustering procedure has been applied to a sample of over two-thousand real journeys made in 2015 and 2016 in all Europe with conventional automobiles; appropriate ranges of distance, time, average speed in urban and extra urban conditions, idle times and stops have been identified thanks to a statistical analysis and the cycle has been created with all of these requirements to be as similar as possible to most of daily trips by road transport. PHEV market has been examined in order to identify the components and architectures that characterize the most registered automobiles; a realistic model has therefore been created and used for the experimental cycle simulation. Simulation results show that PHEV technology has the potential to consume 69% less fuel than a conventional vehicle counterpart with a consequent reduction of 71% in emitted tank-to-wheel (TTW) tons of CO2 and significant reductions in fuel expenditure, in one year, because of the different source of energy

Sustainable Value Proposition Design in a Product-Service System

Many companies have started to add services to their tangible products in order to defend themselves from increased competition from low-cost economies. Research regarding the transition towards product-service systems (PSS) and how the PSS providers' business models are affected exists, but there is a lack of research regarding how the suppliers to the PSS providers are affected by the transition towards PSS. Therefore, this thesis studies the situation for a supplier/partner to an OEM that has changed their business model to a PSS providing one. As the first step in a development of a new business model aims this thesis to provide guidelines for how to set up value propositions suitable for a supplier/partner in this new environment. When technologically complex products, such as aircraft engines, are provided through PSS offerings it is hard to translate customer needs into quality parameters, which makes it hard to sustain the value to customer over time. Therefore, how to keep the value offering sustainable over time is also investigated in this thesis. The aim of this study was to investigate how a sustainable value proposition can be designed for a product and technology supplier/partner to an OEM that offers PSS solutions. The research has been performed through studying relevant literature and collecting empirical data from a case company through semi-structured interviews and a workshop. The case company in this research is Volvo Aero Corporation (VAC). The empirical findings show that VAC wants to offer product-service bundled solution, which fit the whole spectra of PSS value propositions, to their partners/customers. To be able to deliver these different types of product-service bundled solutions different value propositions that suit the different kinds of PSS offerings are needed. Requirements that must be fulfilled to be able to offer and deliver the different types of value propositions exist in terms of securing sufficient information access, aligning the incentives of all actors involved and achieving an internal consensus of what is delivered

An investigation into hybrid power trains for vehicles with regenerative braking

Imperial Users onl