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Hybrid Power for Mobile Systems
Published in Yatish T. Shah, Hybrid Power, 2021
Early commercial application of Li-ion battery technology to vehicles includes the Tesla Roadster, a high-performance sports car. This vehicle, of which about 1,000 have been sold, has a fuel consumption of 0.74 gal/100 miles (energy equivalent basis, EPA combined city/highway). The manufacturer claims a range of 244 miles (also EPA combined city/highway) and a useful battery life of more than 100,000 miles. The base price of $128,000 indicates the continuing problem of battery cost when used in near full-performance vehicles. Tesla announced that it will produce and sell, at about half the price of the Roadster, a five-passenger BEV, the Tesla S, with a range of 160, 230, or 300 miles, depending on optional battery size. Nissan has also announced production of its Leaf EV, a five-passenger car with a range of 100 miles. This vehicle has a Li-ion battery with a total storage capacity of 24 kWh.
Battery EVs and PHEVs
Published in Kwang Hee Nam, and Electric Vehicle Applications, 2017
Mitsubishi announced an EV named “MiEV” which will be commercially available in world market in 2010 [10]. By plug-in charge at home, it takes 7 hours. But at a charging station, it takes 30 minutes for 80% charging. Toyota plans to launch an urban commuter BEV by 2012. Toyota’s FT-EV is targeted to an urban dweller, driving up to 50 miles between home, work and other forms of public transportation. Tesla Roadster is a sports car-type BEV. It utilizes an induction motor, which has a better efficiency in the high-speed region. Specifications of MiEV and Roadster are summarized in Table 13.5.
The Power and Transportation Future
Published in Michael Frank Hordeski, Hydrogen & Fuel Cells: Advances in Transportation and Power, 2020
The Quaranta is a concept hybrid gas/electric vehicle with solar assist. The electric portion is made by Italdesign Giugiaro. The roof is a solar panel that charges the batteries and provides energy for the climate control system. The all wheel drive, mid-engined car accelerates from zero to 62 mph (100 kph) in 4.05 seconds and tops out at 155 mph. This is a three-seat high performance sports car.
Crashworthiness aspects of electric vehicle design
Published in International Journal of Crashworthiness, 2021
A. B. Navale, S. P. Chippa, D. A. Chougule, P. M. Raut
Emma [1] carried out a detailed study that exhibited the wheel energy consumption for three-concept car when subjected to different driving cycles. These concept cars are classified as city car, highway car and sports car based on their weight. Figure 1 illustrates positive and negative wheel energy per driven distance during urban, rural and highway test cycles. The battery energy content for an EV depends upon the respective NEDC cycle range. The calculated wheel energy consumption for the NEDC cycle in Figure 1 states that when an EV is subjected to NEDC cycle, the battery pack of the vehicle must be able to deliver wheel energy of 95 Wh/km for a city car, 122 Wh/km for highway car and 149 Wh/km for a sports car. As the vehicle model used in this work is classified as highway car it must have energy consumption close to 122 Wh/km.
A state-of-the-art review: toward a novel vehicle dynamics control concept taking the driveline of electric vehicles into account as promising control actuators
Published in Vehicle System Dynamics, 2021
Etsuo Katsuyama, Makoto Yamakado, Masato Abe
These examples demonstrate that much torque vectoring research was being carried out for the purpose of stabilising performance at the limits of tyre adhesion. This is because, in principle, driving force distribution control is a particularly effective means of maximising cornering stability as well as acceleration and deceleration forces in regions of high lateral acceleration. The application that can take the most advantage of this characteristic is motor sports. Fetrati et al. applied torque vectoring to a rear-wheel drive sports car with a high rear weight distribution. In addition to a control that boosts yaw response while steering, this research also adopted a control that uses the excess force at the rear wheels to expand the cornering limits and enhance cornering speeds [21]. Another example of research proposed a control law that minimises lap times on a circuit by controlling the distribution of driving force to the four wheels of a race car [22].
Experimental approach to measure the restraining force in deep drawing by means of a versatile draw bead simulator
Published in Materials and Manufacturing Processes, 2019
Elena Bassoli, Antonella Sola, Lucia Denti, Andrea Gatto
Since the metal strip is neither pinched between the male and female parts nor clamped laterally by the thickness shims, the rig relies on a planar stress state and therefore it makes it possible to single out the effect of the draw bead geometry independently of the lateral restrain of the sheet metal. The experimental apparatus, if required, can be operated in lube and dry conditions. The research activity was carried out in close collaboration with a company specialized in the production of sports car chassis. In order to reproduce faithfully the industrial practice, the investigation was performed using the same sheet aluminum metal and the same experimental parameters (including material flow rate through the draw bead) factually applied in sports car production. However the approach proposed here has a general significance, since the DBS can be easily extended to other deep drawing conditions and it can also be addressed to validate computational simulations. In fact, at present the development of specific simulation software and virtual environments to optimize the mold design and processing variables of deep drawing is fostering the diffusion of this technique in industrial production, but it is difficult to define a direct correlation between the forming quality and the forming conditions. Additionally, numerical models must be validated to become reliable and predictive. Therefore robust and versatile experiments are required to prove the validity of the simulations and to enable a correct understanding of the information obtained through such simulations.[21,26]