Driven by the need for lower emissions, better fuel economy and higher efficiency, hybrid vehicles are appearing in many different configurations on today's roadways. While the powertrain components such as the drive motor, motor controller and cooling system are somewhat familiar to the automotive industry, the battery systems are a relatively unfamiliar aspect. This seminar will introduce participants to the concepts of hybrid vehicles, their missions and the role of batteries in fulfilling those requirements.
Unsettled Topics Concerning Airports Cybersecurity Standards and Regulations focuses on four main unsettled domains: the unique characteristics of airports in general, their specific cybersecurity challenges, the missing definitions and conceptual infrastructure for standardization, and finally the regulation of airports cybersecurity. This one includes the gaps in the guides, best-practices, standards and regulation available today. Considering that a typical large international airport is a microcosm of the entire aviation sector, Unsettled Topics Concerning Airports Cybersecurity Standards and Regulations dives deep into the vulnerabilities, lack of cyber-response coordination and information sharing faced by these organizations that have become vital to the global economy.
There is growing interest in the concept of a smart city and how these advanced technologies will improve the quality of living and make a city more attractive to visitors, commerce and industry. This course fills an unmet need for defining and explaining the relationship between connected and autonomous vehicles (CAVs) and smart city transportation. It is apparent that CAVs will achieve the best results when integrated with current and emerging urban infrastructure for transportation. This course addresses such integration from technology, organizational, policy and business model perspectives.
Increasing pollution all over the world has led to stringent emission norms and development of more environment friendly technologies. In near future, rapid transition towards greener and cleaner technologies is anticipated by automotive organisations. In India, FAME (Faster Adoption and Manufacturing of Electric Vehicles) scheme by NITI Aayog has made the intent about the usage of Hybrid & Electric vehicles (EV) clearer. As range is a major concern in EVs, the component that has become the subject of major interest is Battery due to its energy storage ability. Choosing batteries depends on energy density, weight and cost, which makes Li-ion battery technology leading option among others due to its better Power density v/s Energy density relations. For optimum performance and safety, one of the major concerns in the development of lithium-ion (Li-ion) battery packs for EVs is thermal management.
High Fidelity Communication has become a necessity in various sectors. Different wireless data transfer methods play a vital role in various far field and near-field communications. Wireless communication for transferring data through radio spectrum has been a continuously evolving trend, especially in Automotive Sector, with fleet monitoring, platooning and even connected vehicles. Some important parameters considered in selecting a wireless platform would be bandwidth, data transfer, speed and security. Some interesting advantages of communication over the visible spectrum has led to the evolution of Light Fidelity. Implementation of Visible Light Communication (VLC) in the automotive field might enable safer driving conditions through vehicle-to-vehicle (V2V) and vehicle to Infrastructure (V2I) communication with high data transmission rates and efficient-bandwidth usage. The principle of VLC is based on “line of sight” data transmission through modulation of the light source.
Various vehicle manufacturers are launching electric vehicles, which are more sustainable and environmentally friendly. The major component in electric vehicles is the battery, and its performance plays a vital role. Usually the end of life of a battery in the automobile sector is when the battery capacity reaches 80% of its maximum rated capacity. The capacity of a lithium-ion cell decreases with the number of cycles. So, a semi-empirical model is developed for estimating the maximum stored capacity at the end of each cycle. The parameters considered in the model explain the changes in battery internal structure, like capacity losses at different conditions. The capacity estimated using the semi-empirical model is further taken as the inputs for estimating capacity using the Artificial Neural Network (ANN) and Machine Learning (ML) techniques i.e. Linear Regression (LR), Gaussian Process Regression (GPR), Support Vector Machine methods (SVM).
Lithium-Ion batteries are popular for use in EV applications. To improve and understand the use of Lithium-Ion batteries in EV application, present study focused and utilized equivalent circuit models. Model parameters are identified using pulse discharge test carried on 20AH Lithium Iron Phosphate cell. Curve-fitting technique is utilized and detailed procedure to extract model parameters is presented. Models are validated with experimental data of pulse discharge test. Accuracy obtained using 1-RC, 2-RC, 3-RC circuit models is verified and high accuracy of 3RC circuit model can make it act as a battery emulator. Extended Kalman Filter is utilized for estimation of State of Charge of Lithium Iron Phosphate cell. As per our understanding from literature, a good accuracy with low computational burden can be achieved with 1RC model parameters. Therefore, accuracy of SOC estimation using 1RC model parameters is analyzed and effect of initial error in SOC is also observed.
A combustion fuel tank, an internal combustion engine (ICE), and a generator provide the best opportunity to store extra energy onboard battery electric vehicles (BEV). This energy may be used for on-demand electricity production when needed, for example, rural or interstate driving. Specific to this work, the design of a high-efficiency ICE that works at a single speed and a single load, continuously, during the operation of this series hybrid vehicle is considered. The ICE and generator provide a fuel conversion efficiency chemical to electric η~50%. The series hybrid vehicle may deliver miles-per-gallon-of-gasoline (MPG) 13% better than current production plug-in hybrid electric vehicles (PHEV), and miles-per-gallon-of-gasoline-equivalent (MPGe) 12% better than the BEV of the same platform with a larger battery pack to permit capital cities commuting.
Permanent Magnet Synchronous Motor (PMSM) is widely being used in electric vehicle applications due to high-power density and smooth speed control while accelerating as well as braking. Although having a high-power density and mechanical robustness, the motor faces some practical limits to go beyond a certain speed. The speeds fall under the flux weakening region when the motor is expected to operate with constant power output. The limiting points are dictated by motor electrical restrictions even though the motor runs under maximum power with field-oriented vector control (FOC). Such kind of operation is not suitable for an electric vehicle when battery power is available, but the vehicle cannot be accelerated due to insufficient control design. This paper highlights the situations when constant power cannot be maintained in the high-speed region and discusses the possible ways of improvements.
The shift over of the automobile sector from the ICE to the electric drives is imminent due to arising global issues of pollution and ever rising pressure on the demand of the natural resources due to lower efficiency of the ICE drives. This has led to uprising of the Lithium-ion batteries, with addition of the burden of living to expectation of clean energy and higher efficiencies. Alongside, with limitation in the availability of the lithium-ion batteries they carry a hefty price tag with them, hence causing huddles in the research. Lack of research leads to failure of batteries and may cause life threatening situations when operating in the vehicle. In order to insight the working of the cylindrical lithium-ion batteries under different driving and environmental conditions a methodology is developed for the coupled electro-chemical and thermal phenomenon. This allows anticipating the behaviour of the battery under different conditions that influence its performance.
The automobile sector is moving towards electrification as a replacement for the conventional IC Engine as the power source of vehicles. In electric vehicles, Li-ion battery is the widely used energy source for traction and is a major differentiator among various sub components that affect vehicle performance, safety and efficiency. The life of the battery pack is affected by different stress factors like SoC (state of charge), DoD (depth of discharge), C-rates (charge and discharge currents) and battery temperature. Out of the mentioned stress factors, the life of batteries is most influenced by the temperature excursion seen by the li-ion cells in the battery pack. There are various thermal management strategies available to keep the temperature under control like air cooling , chilled liquid cooling and hybrid cooling systems.
The future of bus transit in new millennium is promising. This optimism is based on an anticipated long-term slowdown in growth of suburbs and revitalization of central cities. It reflects and escalates the public concern with traffic congestion, sprawl and pollution. This calls for double the use of public transport to address above issues. It calls for changing the mind-set of society towards public transports like buses, coaches etc. This could happen if bus design ensures right comfort, safety & TCO by ensuring refined bus transport. Hence, it is responsibility of OEMs to provide the new generation buses and coaches, which will ensure the public demands of comforts in terms of NVH refinement. This paper covers the innovative approach used to convert the existing bus NVH refinement to next level as a short-term solution and with the intention of articulating NVH strategies for new generation bus development.
Lithium-ion batteries has emerged as the most suitable option to lead the next wave of automotive revolution. Power density, high energy and packing efficiency are main factors for the currently available alternatives. Battery and cell types face issues which need to be worked upon. Battery thermal management is the main factor affecting the working of the battery due to dynamic operation and range of environments under which they operate.The design as well as the three-dimensional computational fluid dynamics (CFD) simulations were carried out for battery system with and without cooling management from single battery to module level and then to pack level. Initially battery system of 40 kWh/360V was designed with 192 Lithium ion pouch cells (48 modules),weight of 325 kg with overall dimensions of 1550x1190x270mm without any coolant system. The analysis resultant temperature distribution is above the optimal performance battery temperature range (35-55℃)with local heat spots.
As the climate change & CO2 emissions are becoming prime concerns over the globe, Electric Vehicles (EV) are proving to be promising eco-friendly mobility solution. In India, the drive for transition to EV is gaining momentum. Batteries constitute a major chunk of EV cost. Battery Management systems (BMS) are of paramount importance from the aspect of safety, performance, usability & lifetime of EV. Along with fundamental function of monitoring (Cell Voltage, Pack voltage, pack current, cell/pack temperature), BMS must perform function of controlling (Charger/Load Connect, disconnect, Pre-charge) the battery pack in case of failure. In most vehicles, loads & chargers have high capacitance, causing high inrush currents into and from the BMS. This can not only damage the contactors (connect/disconnect circuits) and other load components but also affect the lifetime of cells within battery pack. Conventionally contactor-based cut-off & pre-charge circuits are present in EV's.
Now-a-days, Advanced driver-assistance systems (ADAS) is equipping cars and drivers with advance information and technology to make them become aware of the environment and handle potential situations in better way semi-autonomously. High-quality training and test data is essential in the development and validation of ADAS systems which lay the foundation for autonomous driving technology. ADAS uses the technology like radar, vision and combinations of various sensors including LIDAR to automatize dynamic driving tasks like steering, braking, and acceleration of vehicle for controlled and safe driving. And to integrate these advance technologies, the ADAS needs labeled data to train the algorithm to detect the various objects and moments of driver. Image annotation is one the well-known service to create such training data for computer vision. There are number of open source annotated datasets available viz. COCO, KITTI etc.
Vehicle platooning is a key research area where increased focus and interest is shown to maximize the transport efficiency of road vehicles. Although the key benefits are projected as increased fuel efficiency especially when it comes to commercial vehicles, allied benefits such as convoy pack efficiency, traffic throughput rate, increased life cycle of components and a source of monetary benefit when using a subscription model are areas which need to be explored. Existing literature points to control strategies predominantly focused on longitudinal control and traffic management in bottlenecks.