"Solid-State Batteries to Double Vehicle Range"

At the X Edition of the Nissan Forum in Madrid, experts discussed future automotive trends such as connectivity and autonomous vehicles. Among them was Maarten Sierhuis, Vice President of Global Technology and Innovation at Nissan, who highlighted the technological development pillars for Nissan related to the Ambition 2030 Plan: Electrification, Mobility Innovation, and new mobility experiences.

The head of this department spoke to ABC during a working breakfast prior to the meeting about research being conducted at the Silicon Valley Advanced Technology Center and the potential applications of Artificial Intelligence in both electrification processes and the development and implementation of autonomous driving systems.

These types of investigations take us back to 1999, when the compact Nissan Hyper Mini revolutionised urban mobility with its efficient design and zero emissions. Eleven years later, in 2010, the Nissan Leaf arrived, an electric vehicle with over 4 million units sold worldwide. 2014 saw the E-NV200 van revolutionise commercial transport as the first 100% electric professional vehicle.

The latest arrival is the new Nissan Ariya, which reinvents the sporty electric SUV with over 400 kilometres of range. Thanks to electrification, Nissan has developed advanced technologies that will allow us to drive efficiently and safely without human intervention.

We delved deeper into these issues with Maarten Sierhuis.

"What does electromobility mean for Nissan?"

In the future, I believe we are still limited in the number of kilometres we can travel on a single battery charge. Therefore, one of the new technologies we are developing is a new type of battery, which we call the solid-state battery.

It will provide greater charging capacity, longer range, and, in fact, the cost of the battery will be reduced. This will allow us not only to use the battery for driving but also to store energy and then supply power to a house, building, or facility. These are the types of electrification services we are working on in Silicon Valley, primarily driven by AI, right? We need to optimise energy use, both at home, on the grid, and in our vehicles.

So, that's an area where my office is working on cloud AI technology to understand how people use batteries, their driving style, and then optimise not just my battery but also yours as a fleet of batteries to optimise energy use. So, that's an area where I think the future will drive more electrification, allowing us to reduce CO2 usage and achieve carbon neutrality. Martin, yesterday, a major breakthrough for electromobility development is that we manufacture many electric cars.

"What kind of predictions does AI allow you to make?"

Yes, one of the problems we see today with electric vehicles is that people don't know when the battery's lifespan ends, right? And what is the vehicle's value after using the battery? That's why we're working on second-life batteries, meaning using the vehicle's battery in another application.

This could serve to generate stationary battery storage for a house, neighbourhood, or building, right? But for that, it's necessary to know the state of health of a battery at the end of its life. Currently, it's very difficult to predict because each battery cell has a different state of health. Therefore, the total capacity and health of the battery depend on each battery cell.

And so, what we need to develop is AI technology to determine the current state of health of your car and then provide the customer with a prediction that tells them, well, if you have the car for another three years, this is the state of health after those three years, and this is the value that battery will have for a second life. And so, in some way, this is how we can provide services to both the customer and the second-life market to predict and give certainty about whether you buy this battery after the customer has used it in the vehicle, this is the value of the battery for its second life and maybe even for a third life, right? And this is a circular economy that tries to, you know, move from using the battery for driving to recycling the battery and recycling battery materials to provide this, you know, zero-carbon neutrality, right, by 2050. G

"When will solid-state batteries become a reality?"

Yes, of course, that's a very good question. Nissan has always developed batteries internally, right? In the case of the Leaf, we have internal development. That's why we have a lot of knowledge about batteries in Japan, the research.

Therefore, we are trying to accelerate the development of the materials needed for the solid-state battery, as they must be new and completely different materials. And, of course, cost is very important. Therefore, we are using machine learning, and I will talk about this in my talk this morning.

We hope that by 2028 we will have a first battery ready for SOP. Of course, it depends on many things, but right now we are in the phase where we have a test facility in Japan and are developing the first production line in Yokohama. But our hope is that by 2028 we will have this battery.

The battery itself will be smaller and more compact and, therefore, also lighter, yes. But, to be honest, I still don't know its dimensions. In my office, we are mainly dedicated to researching the materials themselves, finding the right materials to build this battery.

Therefore, we are in a very early phase of actual development research. Moving from material design to the complete battery is a long process involving many people. It's not something my office in Silicon Valley can work on, at least not yet.

"What will be the key material of the future?"

Within the lithium-ion battery, you have the anode and cathode, and then there is liquid electrolyte in the battery. In the future, that liquid electrolyte will become solid material. Of course, what's inside the material is a very secret secret. This is where research and intellectual property are generated within Nissan by doing this.

We use machine learning and simulation. We are one of the few companies with a team of scientists who are experts in materials and machine learning and artificial intelligence. We combine all that and use supercomputers, the largest computers in the United States, with our partners to develop this type of technology.

"The automotive industry is investing heavily in building battery plants. Can this type of infrastructure easily adapt to adopt this new technology, this solid-state battery?"

No, the way the battery is manufactured is completely different. All these processes, the manufacturing and the robots that create them and the ovens must be designed and created. That's what we're working on in Japan, on a manufacturing line for this type of battery.

Of course, we work with many partners. The big challenge after creating the material is creating the manufacturing process, creating these solid materials, and having the safety and everything necessary to manufacture a production battery.

"Electrification is the first step, but then connectivity is the next step. If electric mobility is the gateway to connectivity, how is your team working to make this possible?"

In fact, we are working a lot on this in my office because, as you can imagine, cloud connectivity for cloud computing is very important. The machine learning and artificial intelligence needed to optimise energy distribution between the home, building, and office space are very important.

In reality, we are working on new business models to see this as a way to create new services for our customers. For example, we can provide you with a vehicle and maybe offer you a service that promises you will never run out of electricity while driving. Also, if you use the bidirectional charger at home, maybe with or without solar panels, we can offer you a way to monetise the electricity from your battery to help offset the cost of electricity in your home.

On the other hand, there are office buildings. For example, in my centre, there are over 100 people. Most of them drive an Ariya or a Leaf. Every day they travel from their home to my building.

I have been working with a Silicon Valley startup developing bidirectional chargers for the Ariya and Leaf. We are installing it in my building and connecting it to the power grid. I have posed a challenge to my team. I say I want the electricity cost of my building to be zero at the end of the year. Of course, that's impossible, but you have to say something. We call it the living lab. My building becomes a living lab. Our employees become customers and drive their cars. They come to my building, and we optimise the energy needs of the building and all my employees.

If I am an employee, I come to my building, and when I return home, I need to have enough electricity to get back home. We have to ensure that when we use the electricity from my vehicle in my building, at the end of the day, when I have to drive back to San Francisco, which is over an hour's drive, 80 miles, I have enough energy to return, but not just for me, but for everyone in my office.

Now you can see how things are optimised: when Martin arrives at the office, when Joe arrives at the office, when Jane arrives at the office, how much energy they need to get back home, where they have to go after getting home, whether they go to the supermarket first or drop off their kids. That's why we need to create personalised models of each driver to understand their needs, and then we can have cloud algorithms that optimise everyone's energy consumption. And these AI technologies are what my office is developing, and, in fact, we are doing them for Nissan North America.

Nissan North America is going to launch a service to do this, to offer this type of technology.

"One of the big questions about electric cars is capacity. If we all drive electric cars, does the power grid have a problem?"

In fact, we are working with utility companies to also understand how we balance the grid's needs. The grid can tell us if we need more energy and if your vehicles can return energy to the grid. This way, we can optimise this by knowing what each of our customers is doing, what they need, and then we can return the energy to them.

And with that, maybe we can offset the grid's need, right?, for electric vehicles to provide energy in return. Therefore, I believe that electrification and this type of technology are necessary for both the individual customer and society.

"How is the security of data collected through the connected car and these electric vehicle charging systems ensured?"

Of course, it's very important, right? As you can imagine, the more connectivity we have, the more data we collect, and the more data we know about our customers.

And this has to be secure. And privacy is very important for this. And, as you know, this is part of what we are studying in my lab.

That's why, in my lab, at the Silicon Valley centre, we are creating what I call the research cloud for Nissan, where we study these issues: What security, what data do we store? How long should we keep that data? What data are privacy data that we need to get customer acceptance for? How is this addressed in terms of, you know, getting customer consent to store this data, use it for services? This is what we are studying. And it's a very complicated and difficult topic.

There is no simple answer, but I can assure you that, at Nissan, privacy and security are the most important, just like in your bank and other services you use. I don't think we want to be like social media companies, which will only use the data for what we want to offer you, you know, to use more things, like some of the companies we know do.

"How will autonomous driving evolve?"

It's a really difficult problem. The history of autonomous driving is a story of vision, constant change, and transformation. In recent decades, technology has enabled vehicles to learn to be intelligent machines, seeking safer and more efficient mobility.

Today, Nissan is at the forefront of this evolution. The Simplest Autonomous Mobility platform, developed in collaboration with NASA, not only facilitates autonomous navigation but, thanks to artificial intelligence, creates a constant learning network between vehicles, users, and road infrastructure. This technology improves real-time decision-making, anticipating and solving traffic challenges, minimising accidents, and providing a 100% safe experience.

Nissan leads the way towards a new model of smarter, safer, and more sustainable mobility. The future drives itself. I would say that in the case of Spain, we know that 90% of accidents worldwide are due to human errors. So if we can, with autonomous driving, reduce that 90% of accidents, apart from saving many lives, it will also have a significant impact in terms of savings for society. There are studies showing up to 10 billion euros in savings if we were able to reduce that 90% of accidents.

At Nissan, we started working on autonomous driving a long time ago. In fact, more than 10 years ago, we introduced the foundation of the technology with the 360 camera, and, in fact, we are working to introduce it in 2027. And here I stop because he is the true father of all these technologies that we are developing to be able to introduce autonomous driving. I can tell you that the reason I started working at Nissan in 2013 to open its research centre in Silicon Valley was because I wanted to work in the field of autonomous driving and change the world for the better. Although autonomous driving has been a long process, everyone thought it would arrive soon.

Experts knew it wasn't so easy to develop, but I think we are about to experience a huge change in the world of mobility. At Nissan, we always said it was a step-by-step approach, where everyone, especially in the media, said we would have autonomous cars in 2015 first and then in 2020, and we are still waiting.

But Nissan always said that safety is the most important part of autonomous technology. We develop autonomy to offer a safer driving experience and reduce accidents. That is our number one priority.

"How has Nissan's evolution in autonomous driving been?"

We started with ProPilot 1 and now with ProPilot 2, where we can drive hands-free on the highway and change lanes hands-free, but always with eyes on the road. First of all, in Silicon Valley, we are developing the software, the AI capabilities for Nissan to provide this technology for the next level of ADAS system that is coming. There are increasingly difficult situations, not only on the highway but also in cities and off the highway, as we say, or urban environments.

There is increasing interaction with pedestrians, cyclists, motorcyclists, and other forms of mobility. And there is more need for what we call perception. More and more sensors are needed, LIDAR, not just radars and cameras, but also LIDAR. One of the really difficult technologies we need to develop is ensuring that we always avoid colliding with an object we see around us. Emergency manoeuvres to avoid an object, especially when driving at high speed, are incredibly difficult.

That's simply a fact: it's about seeing far enough ahead the speed at which you're travelling, the speed at which an object is approaching you. All this means you have to be able to make a decision in 10, 15, 20 milliseconds. Making that calculation, even with machine learning, is very, very difficult.

The amount of computing done in the vehicle must improve and increase, and that's what we're working on. On the other hand, I think everyone knows that in the automotive world, it's not a software world. We have to bring the automotive world into the software world.

For example, we can't afford to have several different software systems for each type of ADAS or for the entire range of autonomy, up to level 4, driverless autonomy. We need a software platform. In Silicon Valley, we are working to develop it.

We call it the reference software architecture for autonomous driving that we can apply to ADAS systems, the next level of professional autonomous driving, as well as level 4 hands-free driving. What is different in these vehicles is perhaps the computing needed in the vehicles, but also the type of sensors. If you have a human who is still responsible for their eyes, maybe hands-free, but with eyes on the road, you can reduce the need for sensors.

But, as soon as you want to drive through cities, you need maps, you need LIDAR and radar and camera fusion, and that's what you need for both the next level of ADAS and the level 4 driver who, over time, doesn't need any hands-free intervention. We are developing that software platform for Nissan in Silicon Valley.

"Is there any way to measure this economic impact of autonomous driving?"

We are not business people, but, as you said, technology has to have a purpose, and therefore, there has to be an understanding of the value that can be created with this new technology.

So, together with the team, the business team of Nissan North America and Japan, we have analysed the robot taxi market. If you are a journalist, I'm sure you are reading what's happening in San Francisco. Last week, now we have San Francisco and Los Angeles, where people can ride in a robot taxi, which is a level 4 driving experience outside the car.

So, if you analyse that market and compare the market of what we call driver transportation services, like Uber and Lyft, with other types of mobility services, we believe the robot taxi market will surpass this type of market. And we are talking about the global market, and this is where it becomes really difficult because no one knows how long it will take or what the real business models that will develop are. But the current market value, according to some people, like McKinsey estimates, is between 400 and 500 billion dollars worldwide.

In the United States, we believe it's about 190 billion dollars, just for the robot taxi market by 2040. Therefore, we are seeing that worldwide 1.5, 1.2, or 1.4 million robot taxis could be sold by 2040. And that is a huge value.

And, of course, everything else that is created from there is part of this calculation. It's very difficult to predict.