Opportunities and risks for CO2 intense sectors in Turkey

The Carbon Disclosure Project (CDP) is an independent not-for-profit organization holding the largest database of primary corporate climate change information in the world. Over 3,000 organizations in some 60 countries now disclose their greenhouse gas emissions, water management and climate change strategies through CDP, in order that they can set reduction targets and make performance improvements. This data is gathered on behalf of institutional investors, purchasing organizations and government bodies, then, made available to CDP signatories for integration into business and policy decision-making. Since its formation in 2000, CDP has become the gold standard for carbon disclosure methodology and process, providing essential climate change data to the global market place. Since the beginning of the year 2010, Turkey is included in Carbon Disclosure Project with the support of Akbank and Ernst & Young-Turkey. The project is managed and controlled by Sabanci University Corporate Governance Forum, which has become a centre of expertise on corporate disclosure over the years. 50 companies, which constitute the Istanbul Stock Exchange’s ISE-50 index, have been invited by CDP Turkey in the year of 2010 to disclose climate change related information,10 of those companies responded to CDP’s invitation and presented their carbon emission levels and risk management strategies to international investors through the CDP platform. Additionally one company joined the CDP voluntarily. In the year 2011, the invitation is extended to 100 companies constituting Istanbul Stock Exchange’s ISE-100 index. A total of 17 ISE 100 companies responded to CDP, including two ISE 100 firms whose international parent companies answered the questionnaire on their behalf. In addition, there are three voluntary responses outside the ISE 100 sample, which increased the number of direct CDP responses from Turkish companies to 20. In 2012, CDP Turkey aims to enlarge its scope to cover both listed and non-listed firms in carbon intense industries through voluntary disclosure in collaboration with sector organizations. This report discusses the conditions in CO2 intense sectors of Turkey, in terms of market conditions, current & potential regulatory risks and opportunities. The first sections of the report elaborate on comparative GHG emission trends in Turkey. The second section lays down leading firms in the largest industries and the most CO2 intensive sectors in Turkey. The third section draws attention to the market dynamics in carbon intense industries. And the last section, points out risks and potential opportunities for those industries, including EC legislation and initiatives to transform consumption and production patterns

Modular switched reluctance machines to be used in automotive applications

In the last decades industry, including also that of electrical machines and drives, was pushed near to its limits by the high market demands and fierce competition. As a response to the demanding challenges, improvements were made both in the design and manufacturing of electrical machines and drives. One of the introduced advanced technological solutions was the modular construction. This approach enables on a hand easier and higher productivity manufacturing, and on the other hand fast repairing in exploitation. Switched reluctance machines (SRMs) are very well fitted for modular construction, since the magnetic insulation of the phases is a basic design requirement. The paper is a survey of the main achievements in the field of modular electrical machines, (especially SRMs), setting the focus on the machines designed to be used in automotive applications

Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles

The combination of machine learning and heterogeneous embedded platforms enables new potential for developing sophisticated control concepts which are applicable to the field of vehicle dynamics and ADAS. This interdisciplinary work provides enabler solutions -ultimately implementing fast predictions using neural networks (NNs) on field programmable gate arrays (FPGAs) and graphical processing units (GPUs)- while applying them to a challenging application: Torque Vectoring on a multi-electric-motor vehicle for enhanced vehicle dynamics. The foundation motivating this work is provided by discussing multiple domains of the technological context as well as the constraints related to the automotive field, which contrast with the attractiveness of exploiting the capabilities of new embedded platforms to apply advanced control algorithms for complex control problems. In this particular case we target enhanced vehicle dynamics on a multi-motor electric vehicle benefiting from the greater degrees of freedom and controllability offered by such powertrains. Considering the constraints of the application and the implications of the selected multivariable optimization challenge, we propose a NN to provide batch predictions for real-time optimization. This leads to the major contribution of this work: efficient NN implementations on two intrinsically parallel embedded platforms, a GPU and a FPGA, following an analysis of theoretical and practical implications of their different operating paradigms, in order to efficiently harness their computing potential while gaining insight into their peculiarities. The achieved results exceed the expectations and additionally provide a representative illustration of the strengths and weaknesses of each kind of platform. Consequently, having shown the applicability of the proposed solutions, this work contributes valuable enablers also for further developments following similar fundamental principles.Some of the results presented in this work are related to activities within the 3Ccar project, which has received funding from ECSEL Joint Undertaking under grant agreement No. 662192. This Joint Undertaking received support from the European Union’s Horizon 2020 research and innovation programme and Germany, Austria, Czech Republic, Romania, Belgium, United Kingdom, France, Netherlands, Latvia, Finland, Spain, Italy, Lithuania. This work was also partly supported by the project ENABLES3, which received funding from ECSEL Joint Undertaking under grant agreement No. 692455-2

Energy-storage technologies and electricity generation

As the contribution of electricity generated from renewable sources (wind, wave, solar) grows, the inherent intermittency of supply from such generating technologies must be addressed by a step-change in energy storage. Furthermore, the continuously developing demands of contemporary applications require the design of versatile energy-storage/power-supply systems offering wide ranges of power density and energy density. As no single energy-storage technology has this capability, systems will comprise of combinations of technologies such as electrochemical supercapacitors, flow batteries, Lithium-ion batteries, superconducting magnetic energy storage (SMES) and kinetic energy storage. The evolution of the electrochemical supercapacitor is largely dependent on the development of optimised electrode materials (tailored to the chosen electrolyte) and electrolytes. Similarly, the development of Lithium-ion battery technology requires fundamental research in materials science aimed at delivering new electrodes and electrolytes; Lithium-ion technology has significant potential and a step-change is required in order to promote the technology from the portable electronics market into high-duty applications. Flow-battery development is largely concerned with safety and operability. However, opportunities exist to improve electrode technology yielding larger power densities. The main barriers to overcome in terms of the development of SMES technology are those related to high-temperature superconductors in terms of their granular, anisotropic nature. Materials development is essential for the successful evolution of flywheel technology. Given the appropriate research effort, the key scientific advances required in order to successfully develop energy-storage technologies generally represent realistic goals which may be achieved by 2050

Electronics Thermal Management in Information and Communications Technologies: Challenges and Future Directions

This paper reviews thermal management challenges encountered in a wide range of electronics cooling applications from large-scale (data center and telecommunication) to smallscale systems (personal, portable/wearable, and automotive). This paper identifies drivers for progress and immediate and future challenges based on discussions at the 3rd Workshop on Thermal Management in Telecommunication Systems and Data Centers held in Redwood City, CA, USA, on November 4–5, 2015. Participants in this workshop represented industry and academia, with backgrounds ranging from data center thermal management and energy efficiency to high-performance computing and liquid cooling, thermal management in wearable and mobile devices, and acoustic noise management. By considering a wide range of electronics cooling applications with different lengths and time scales, this paper identifies both common themes and diverging views in the thermal management community

A H2 PEM fuel cell and high energy dense battery hybrid energy source for an urban electric vehicle

Electric vehicles are set to play a prominent role in addressing the energy and environmental impact of an increasing road transport population by offering a more energy efficient and less polluting drive-train alternative to conventional internal combustion engine (ICE) vehicles. Given the energy (and hence range) and performance limitations of electro-chemical battery storage systems, hybrid systems combining energy and power dense storage technologies have been proposed for vehicle applications. The paper discusses the application of a hydrogen fuel cell as a range extender for an urban electric vehicle for which the primary energy source is provided by a high energy dense battery. A review of fuel cell systems and automotive drive-train application issues are discussed, together with an overview of the battery technology. The prototype fuel cell and battery component simulation models are presented and their performance as a combined energy/power source assessed for typical urban and sub-urban driving scenario

Electric vehicle possibilities using low power and light weight range extenders

Electric cars have the disadvantage of a limited range, and drivers may experience a range anxiety. This range anxiety can be solved by adding a range extender. But, the range extender should be light so as not to significantly increase the weight of the original vehicle. In urban areas with dense traffic (usually developing countries), the average speed around cities is typically lower than 50km/h. This means, the rolling resistance losses are more important than aerodynamic losses, and a weight reduction results in a bigger electrical range. Therefore, smaller and lighter range extenders are of much interest. The contribution of this paper is to indicate the possibility of range extenders with less than 25 kg with a capacity of 150 to 200 cc to suit a condition where weight counts. In this paper, the cost, environmental and grid impacts of going electric are also discussed. The effect of high altitude and driving style on the performance of an electric vehicle is assessed. The challenges and opportunities of vehicle electrification between countries with decarbonated power generation and fossil fuel dominated power generation are highlighted. Throughout the article, the case of Ethiopia is taken as an example

GA-tuning of nonlinear observers for sensorless control of automotive power steering IPMSMs

The paper considers two observer-based rotor position estimation schemes for sensorless control of interior permanent magnet synchronous motors (IPMSMs) for use in future automotive power steering systems. Specifically, emphasis is given to techniques based on feedback-linearisation followed by classical Luenberger observer design, and direct design of non-linear observers. Genetic algorithms (GAs), using the principles of evolution, natural selection and genetic mutation, are introduced to address difficulties in selecting correction gains for the observers, since no analytical tuning mechanisms yet exist. Experimental measurements from an automotive power steering test-facility are included, to demonstrate the enhanced performance attributes offered by tuning the proposed observer schemes, online, in this manner

Hybrid energy sources for electric and fuel cell vehicle propulsion

Given the energy (and hence range) and performance limitations of electro-chemical batteries, hybrid systems combining energy and power dense storage technologies have been proposed for electric vehicle propulsion. The paper will discuss the application of electro-chemical batteries, supercapacitors and fuel cells in single and hybrid source configurations for electric vehicle drive-train applications. Simulation models of energy sources are presented and used to investigate the design optimisation of electric vehicle on-board energy source in terms of energy efficiency and storage mass/volume. Results from a case study considering a typical small urban electric vehicle are presented, illustrating the benefits of hybrid energy sources in terms of system mass and vehicle range. The models and approach can be applied to other vehicles and driving regimes