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Nissan unveils new Leaf – and new era

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Nissan yesterday introduced the new Nissan Leaf, the next version of its zero-emission electric vehicle. The Leaf will now offer drivers a range of up to 400km and uses a 110kW motor.

The Nissan LEAF has been completely reinvented, combining greater range with a dynamic new design and advanced technologies*, representing Nissan’s technological leadership.

“The new Nissan LEAF drives Nissan Intelligent Mobility, which is the core brand strategy for Nissan’s future,” said Hiroto Saikawa, president and chief executive officer of Nissan. “The new Nissan LEAF, with its improved range, combined with the evolution of autonomous drive technology such as ProPILOT Park, and the simple operation of the e-Pedal, strengthens Nissan’s EV leadership as well as the expansion of EVs globally. It also has core strengths that will be embodied by future Nissan models.”

The most advanced e-powertrain

The new Nissan LEAF offers a range of 400 km, allowing drivers to enjoy a safer and longer journey. The new e-powertrain gives the new Nissan LEAF 110 kW of power output and 320 Nm of torque, improving acceleration and driver enjoyment.

Evolved autonomous drive technologies

The new LEAF features ProPILOT autonomous drive technology, used during single-lane driving on the highway.

It also offers ProPILOT Park. When activated, the car’s ProPILOT Park technology takes control of steering, acceleration, braking, shift-changing and the parking brake to automatically guide it into a parking spot. It enables the driver to park safely and simply, even when parallel parking.

e-Pedal to reduce stress

The new LEAF’s revolutionary e-Pedal technology transforms the way people drive. It lets drivers start, accelerate, decelerate and stop by increasing or decreasing the pressure applied to the accelerator. When the accelerator is fully released, regenerative and friction brakes are applied automatically, bringing the car to a complete stop. The car holds its position, even on steep uphill slopes, until the accelerator is pressed again. The reactiveness of the e-Pedal maximizes EV driving pleasure.

Exterior design: sleek silhouette and “cool tech attitude”

The new Nissan LEAF’s design includes a low, sleek profile that gives it a sharp, dynamic look. Along with excellent aerodynamics, the styling – from the sleek silhouette to the car’s “advanced expression” – evokes the exhilaration of driving an EV.

Familiar Nissan design features include the signature boomerang-shaped lamps and V-motion flow in the front. The flash-surface grille in clear blue and the rear bumper’s blue molding identify the car as a Nissan EV.

Interior design: premium ambience with a clean, relaxed, high-tech feeling

The new Nissan LEAF’s completely redesigned cabin is focused on the driver, featuring a front panel in the form of a “gliding wing.” It combines an excellent use of space with functionality.

The interior design creates a relaxed ambience and premium quality feel, due to carefully selected materials. Vibrant blue stitching in the seats, dashboard and steering wheel has been incorporated as a symbol of Nissan’s electric vehicles. The 7-inch, full-color (TFT) display has been redesigned to highlight key features, such as the Safety Shield technology power gauge and audio and navigation system information. Apple CarPlay has also been added.

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For customers who want more excitement and performance, Nissan will also offer a version with more power and longer range at a higher price in 2018 (timing may vary by market).

The new Nissan LEAF will go on sale Oct. 2 in Japan. The model is slated for deliveries in January 2018 in the U.S., Canada and Europe. It will be sold in more than 60 markets worldwide.

2017 Nissan LEAF specifications (Japan model)

Specifications are based on the latest product information available at the time of release. Specifications for other regions will be announced at the start of sales.

2017 Nissan LEAF specifications (Japan model)
Specifications are based on the latest product information available at the time of release. Specifications for other regions will be announced at the start of sales.

Exterior
Overall length 4,480 mm
Overall width 1,790 mm
Overall height 1,540 mm
Wheelbase 2,700 mm
Track width front/rear 1,530-1,540 mm/1,545-1,555 mm
Minimum ground clearance 150 mm
Coefficient of drag 0.28 Cd
Tires 205/55R16 or 215/50R17
Cargo area (VDA) 435 L

 

Weight/capacity
Curb weight 1,490-1,520 kg
Capacity 5 passengers
Gross vehicle weight 1,765-1,795 kg

 

Battery  
Type Li-ion battery
Capacity 40 kWh

 

Electric motor  
Name EM57
Maximum output 110 kW (150ps)/3283~9795 rpm
Maximum torque 320 N・m (32.6kgf・m)/0~3283 rpm

 

Performance  
Cruising range 400km (JC08)
Charging time (normal charging) 16 hours (3 kW)
8 hours (6 kW)
Charging time from alert to 80% (quick charging) 40 minutes

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Project Bloodhound saved

The British project to break the world landspeed record at a site in the Northern Cape has been saved by a new backer, after it went into bankruptcy proceedings in October.

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Two weeks ago,  and two months after entering voluntary administration, the Bloodhound Programme Limited announced it was shutting down. This week it announced that its assets, including the Bloodhound Supersonic Car (SSC), had been acquired by an enthusiastic – and wealthy – supporter.

“We are absolutely delighted that on Monday 17th December, the business and assets were bought, allowing the Project to continue,” the team said in a statement.

“The acquisition was made by Yorkshire-based entrepreneur Ian Warhurst. Ian is a mechanical engineer by training, with a strong background in managing a highly successful business in the automotive engineering sector, so he will bring a lot of expertise to the Project.”

Warhurst and his family, says the team, have been enthusiastic Bloodhound supporters for many years, and this inspired his new involvement with the Project.

“I am delighted to have been able to safeguard the business and assets preventing the project breakup,” he said. “I know how important it is to inspire young people about science, technology, engineering and maths, and I want to ensure Bloodhound can continue doing that into the future.

“It’s clear how much this unique British project means to people and I have been overwhelmed by the messages of thanks I have received in the last few days.”

The record attempt was due to be made late next year at Hakskeen Pan in the Kalahari Desert, where retired pilot Andy Green planned to beat the 1228km/h land-speed record he set in the United States in 1997. The target is for Bloodhound to become the first car to reach 1000mph (1610km/h). A track 19km long and 500 metres wide has been prepared, with members of the local community hired to clear 16 000 tons of rock and stone to smooth the surface.

The team said in its announcement this week: “Although it has been a frustrating few months for Bloodhound, we are thrilled that Ian has saved Bloodhound SSC from closure for the country and the many supporters around the world who have been inspired by the Project. We now have a lot of planning to do for 2019 and beyond.”

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Motor Racing meets Machine Learning

The futuristic car technology of tomorrow is being built today in both racing cars and
toys, writes ARTHUR GOLDSTUCK

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The car of tomorrow, most of us imagine, is being built by the great automobile manufacturers of the world. More and more, however, we are seeing information technology companies joining the race to power the autonomous vehicle future.

Last year, chip-maker Intel paid $15.3-billion to acquire Israeli company Mobileye, a leader in computer vision for autonomous driving technology. Google’s autonomous taxi division, Waymo, has been valued at $45-billion.

Now there’s a new name to add to the roster of technology giants driving the future.

DeepRacer on the inside

Amazon Web Services, the world’s biggest cloud computing service and a subsidiary of Amazon.com,  last month unveiled a scale model autonomous racing car for developers to build new artificial intelligence applications. Almost in the same breath, at its annual re:Invent conference in Las Vegas, it showcased the work being done with machine learning in Formula 1 racing.

AWS DeepRacer is a 1/18th scale fully autonomous race car, designed to incorporate the features and behaviour of a full-sized vehicle. It boasts all-wheel drive, monster truck tires, an HD video camera, and on-board computing power. In short, everything a kid would want of a self-driving toy car.

But then, it also adds everything a developer would need to make the car autonomous in ways that, for now, can only be imagined. It uses a new form of machine learning (ML), the technology that allows computer systems to improve their functions progressively as they receive feedback from their activities. ML is at the heart of artificial intelligence (AI), and will be core to autonomous, self-driving vehicles.

AWS has taken ML a step further, with an approach called reinforcement learning. This allows for quicker development of ML models and applications, and DeepRacer is designed to allow developers to experiment with and hone their skill in this area. It is built on top of another AWS platform, called Amazon SageMaker, which enables developers and data scientists to build, train, and deploy machine learning quickly and easily.

Along with DeepRacer, AWS also announced the DeepRacer League, the world’s first global autonomous racing league, open to anyone who orders the scale model from AWS.

DeepRacer on the outside

As if to prove that DeepRacer is not just a quirky entry into the world of motor racing, AWS also showcased the work it is doing with the Formula One Group. Ross Brawn, Formula 1’s managing director of Motor Sports, joined AWS CEO Andy Jassy during the keynote address at the re:Invent conference, to demonstrate how motor racing meets machine learning.

“More than a million data points a second are transmitted between car and team during a Formula 1 race,” he said. “From this data, we can make predictions about what we expect to happen in a wheel-to-wheel situation, overtaking advantage, and pit stop advantage. ML can help us apply a proper analysis of a situation, and also bring it to fans.

“Formula 1 is a complete team contest. If you look at a video of tyre-changing in a pit stop – it takes 1.6 seconds to change four wheels and tyres – blink and you will miss it. Imagine the training that goes into it? It’s also a contest of innovative minds.”

AWS CEO Andy Jassy unveils DeepRacer

Formula 1 racing has more than 500 million global fans and generated $1.8 billion in revenue in 2017. As a result, there are massive demands on performance, analysis and information. 

During a race, up to 120 sensors on each car generate up to 3GB of data and 1 500 data points – every second. It is impossible to analyse this data on the fly without an ML platform like Amazon SageMaker. It has a further advantage: the data scientists are able to incorporate 65 years of historical race data to compare performance, make predictions, and provide insights into the teams’ and drivers’ split-second decisions and strategies.

This means Formula 1 can pinpoint how a driver is performing and whether or not drivers have pushed themselves over the limit.

“By leveraging Amazon SageMaker and AWS’s machine-learning services, we are able to deliver these powerful insights and predictions to fans in real time,” said Pete Samara, director of innovation and digital technology at Formula 1.

  • Arthur Goldstuck is founder of World Wide Worx and editor-in-chief of Gadget.co.za. Follow him on Twitter on @art2gee and on YouTube

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