Nissan Motor this week introduced its new drive system called e-POWER to customers. It marks the first time that e-POWER technology is available for consumers, marking a significant milestone in the electrification strategy under Nissan Intelligent Mobility.
e-POWER borrows from the EV technology perfected in the Nissan LEAF, the best-selling pure electric car in history, with more than 250,000 units sold. Unlike the LEAF, e-POWER adds a small gasoline engine to charge the high-output battery when necessary, eliminating the need for an external charger while offering the same high-output.
The technology of e-POWER
The e-POWER system features full electric-motor drive, meaning that the wheels are completely driven by the electric motor. The power from a high-output battery is delivered to the e-POWER’s compact powertrain comprised of a gasoline engine, power generator, inverter, and a motor. In conventional hybrid systems, a low-output electric motor is mated to a gasoline engine to drive the wheels when the battery is low (or when traveling at high speeds). However, in the e-POWER system, the gasoline engine is not connected to the wheels; it simply charges the battery. And unlike a full EV, the power source originates from the engine and not just the battery.
This system structure generally requires a bigger motor and battery because the motor is the only direct source to drive wheels. This has made it hard for the automotive industry to mount the system in compact cars. However, Nissan has cracked the code and learned how to minimize and reduce weight, develop more responsive motor control methods and optimize energy management. As a result, e-POWER uses a smaller battery than the LEAF, but delivers the same driving experience as a full EV.
The benefits of e-POWER
e-POWER delivers massive torque almost instantly, which enhances drive response and results in smooth acceleration. Also, the system operates very quietly, much like a full EV. Because e-POWER relies on the engine much less frequently, its fuel efficiency is comparable to that of leading conventional hybrids, especially during around-the-town commutes. The e-POWER system allows you to enjoy all the benefits of an EV without having to worry about charging the battery.
Nissan is actively pursuing a zero-emission, zero-fatality world for driving through its EV program and autonomous drive technology. To make this vision a reality, Nissan is developing “Nissan Intelligent Mobility,” which anchors critical company decisions around how cars are powered, how cars are driven, and how cars integrate into society, all while staying focused on creating more enjoyable driving experiences. e-POWER is another step towards achieving our zero-emission vision through a new and more efficient electric powertrain.
In 2006, Nissan experienced a breakthrough in its energy management technology. Nissan’s engineers were able to reduce the battery capacity to match its competitors’ hybrid vehicles while still delivering desirable EV qualities, such as quietness and efficient energy use. In addition, application of Nissan’s technologies, such as the integration of a power-generating engine, electric motor drive for compact car use, strengthening of the powertrain’s rigidity and improvements in NVH levels, became the foundation of e-POWER and its implementation in the compact-car segment.
Nissan is committed to developing electric-powered powertrains that use various fuels to cater to the different requirements of the world’s markets. e-POWER is but one example of that quest and will strengthen Nissan’s lineup of electric-powered powertrains. Nissan is also conducting research and development of the SOFC (Solid Oxide Fuel Cell) fuel-cell vehicle, and will continue to introduce innovative new products into various areas and promote the worldwide use of EVs.
Note: The e-POWER system is classified as a series hybrid. The Note e-POWER represents the first mass-production compact segment car ever to be equipped with a series hybrid system.
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.
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.”
Motor Racing meets Machine Learning
The futuristic car technology of tomorrow is being built today in both racing cars and
toys, writes ARTHUR GOLDSTUCK
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.
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.
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.”
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.