UCL Engineering


IM@UCL: The Podcast - Transcript - Episode 6

We’re exploring the transition from manual to self-driving vehicles. This podcast series explores the multi-disciplinary research that will impact us all.
Once a month, join Cassidy Martin on a journey of self-driving discovery. Each episode will feature members of the multidisciplinary research team at IM@UCL that will revolutionise the future of driving.  

Episode 6: From Land to Sea: Eco-Friendly Vehicular Design

Cassidy: Hello and welcome to IM@UCL: The Podcast, a podcast about the research at UCL that will revolutionise the future of driving. My name is Cassidy Martin, and I am your host on this journey of self-driving discovery.

Sometimes in life it feels like if only this one thing was different, life would be so much better. For instance, if only I had an electric bike, I would be able to get around the city so much faster. If only I had a leisure centre nearby, I would be in much better shape. If only Lasik didn’t cost so much, I wouldn’t have to wear glasses all the time. These are a few of the somewhat ridiculous if onlys I tell myself. We all have our own versions, right? Well academic research can also often have their own if onlys, which is certainly the case in this month’s episode. 

I spoke with two academics who are focused on different if onlys of the transport world. Our first guest feels that if only we were able to create magnetic energy without magnets, we would be much better equipped to transition from petrel to electric powered vehicles. And the next guest feels that if only there was a way for autonomous ship and boat designers to test their vessels in the lab before in open water, their research would be more economical and have a higher success rate once in the water.

Let’s get started.

Mehdi: Hello, this is Mehdi Baghdadi. I am a lecturer in electric propulsion at the Mechanical Engineering Department. And I'm also a Co-Director of Advanced Propulsions at UCL East. 
Cassidy: Electric propulsion, Mehdi’s research area, are essentially the parts of electric vehicles that propel it into motion. And one aspect of his team’s research has been centred around a very crucial part of electric propulsions, magnetic energy. When you charge an electric vehicle, you are feeding electric energy into the car. This electric energy then goes through a conversion process in the car, changing to magnetic energy, then to mechanical energy, allowing the vehicle to move. So, if you want an electric vehicle to move, you need to have permanent magnets for the magnetic energy conversion part of the process. But the problem is, there is a limited supply of them. 

Mehdi: So, we have permanent magnets – I'm sure that you've seen magnets – the problem with those magnets is that they're dry earth materials, which means that there are not many of them around and they’re very precious. And the sources that those magnets are coming from are very limited to some part of some specific country. So, they are very limited. So, if we use all of them, there are no other magnets around which could be quite problematic.

Cassidy: And this is an issue when countries want to replace fuel powered vehicles with electrically powered ones. For instance, at the COP26 summit, the big climate change conference that took place in Glasgow in 2021, there was a declaration to accelerate the transition of selling exclusively zero emission vans and cars by 2040, and no later than 2035 for leading markets. And in the UK, they are looking at having all new cars sold to be electric by 2030. But this transition will be impossible if an alternative for magnetic energy is not used. The good news is there is an alternative, but it’s complicated.

Mehdi: We have some other type of motors that can use some fancy materials called superconducting materials inside the motor. So, for those types of materials, they’re quite challenging because normally superconductors work in a very low temperature, liquid nitrogen, boiling temperature about 77 Kelvin, something like that. And if you want to use superconductors inside the motor, you need to consider many different aspects. Such as how electrically superconductors behave, but how you can keep them cool down at a very low temperature for a long time. And last but not least, how different parts of your motor behave in the low temperature. For example, if you cooled down a metal or a plasti, both of them shrink but the amount of the shrink of the, let's say metals, is more than some sort of plastics for instance. So, if you put them together, and then you cooled them all down to minus 200 degrees Celsius, then you need to consider how, because you have a different shrinking ratio, how they can function properly in that low temperature. But the good point about superconductors is that if you could keep the temperature low, you can magnetise them and then they behave like a permanent magnet, which is very nice. So, you can make a permanent magnet by using superconductors. The problem is that they can get demagnetized in certain conditions. So, one of the tasks that we've had before, it started when I was at Cambridge, was to try to understand how these superconductors behave and how we can try to avoid or reduce the amount of demagnetisation. But if you could magnetise them and if you could avoid demagnetisations on superconductors, then you can use them inside the motor. And then you will end up with a highly efficient and very compact type of electric motors.

Cassidy: Speaking of things being compact, another aspect of Mehdi and his team’s research is on making things more compact.

Mehdi: We are trying to develop more efficient and more compact units. Not only for the electric cars, but also for other types of electric vehicles, such as air taxis, or electric ships, etc. 

Cassidy: What would be some of the benefits of making it more compact?

Mehdi: It depends on the application. For example, if you want to use the electric propulsion unit in a ship, for instance, compactness is not your main criteria for the design. You would like to have for a ship, for example, something highly reliable. You don't want your system to stop working in the middle of the ocean. But in some other applications, such as electric taxis, for instance, you have very limited space. And then most of the time you need to especially as A: is limited, and B: if you have small systems, you have more space for batteries. So, batteries are quite precious to have, the more the better for the operation of your system. In that type of condition, space becomes quite precious and valuable. 

Cassidy: Yeah, yeah. That's interesting that you said, ‘having more space for a battery’. Which makes sense because, yeah, you want that big battery so that you can go longer periods of time without charging up cause my brain automatically went to more room for passengers, but I didn't think about that. That's so true. 

In an article by Tomos Morgan for the BBC titled “How easy is it to drive across Wales in an electric car?”, Tomas found his drive across Wales extremely challenging. There was a lot of planning involved, and even with careful planning, he still nearly ran out of a charge at one point. There were also hours spent looking for and charging his car when the place he stayed at did not have a charging point in town. Additionally, rapid chargers (chargers that can charge in under an hour) were even fewer and farther between. This makes that need for a powerful battery extremely important. 

In a further quest to have a longer charge. Mahdi’s team is trying to solve the problem with an alternative power source. 

Mehdi: So, we can have something which is called electric hybrid cars, which means that you can have different energy resources. So, the main one is batteries for instance. So, we can have some energy inside the batteries. And then we have the fuel cells that work basically based on the hydrogen. And hydrogen you can access quite cheaply and they’re quite clean as well.

Cassidy: When you put hydrogen in a car, can you put it in a car like you would fuelling gas into a car?

Mehdi: Precisely, yeah, so there are some sort of hydrogen stations that you can go and then fill up your tank with hydrogen, and then some chemical reactions will happen inside your car. And the outcome would be some energy that you can use to run your motor and also some water. So compared with the internal combustion engine, it gets some CO2 or CH4 as an outcome. So, you get some water which is a much safer energy resource compared with fuels, gas, etc.

Cassidy: So, when it's coming out, is it coming out as water? And then it's using like hydrogen for certain parts of it? And then the oxygen or whatever else for the other parts? Am I understanding that correctly?

Mehdi: Yeah, exactly. Yeah, so you have hydrogen and then you have oxygen. And then when you have these combinations, as a chemical reaction, you get some energy out and then you get water out. 

Cassidy: So in summary, Mehdi’s research team is looking into how to create magnetic energy to run electric motors without the use of hard to acquire magnets; to create smaller, more efficient batteries, so you can fit more of them into vehicles allowing them to go for longer periods without charging; and powering vehicles in a hybrid approach of electric charging and hydrogen fuel. All of this will help electric vehicles to be mass produced, run efficiently and, most importantly, lessen the environmental impact of driving. At this point you may be asking yourself where the IM@UCL facility fits into all of this. Well…

Mehdi: Bani and her group did a fantastic job to build this car simulator. And what they do is basically they try to understand the driver’s behaviour, more or less, in the virtual that is close to real conditions. And so, what we do here is trying to understand how we can build, let's say, electric motors and power electric systems that are highly efficient. And electric motors for instance, they do not work under one condition. For example, sometimes you are in highways so you can go to 120 miles per hour, or even more. Sometimes you're in the urban area that you can go with 40/50 miles per hour. Sometimes you need to have a sudden break, sometimes you need to accelerate your car very quickly based on your different modes or different environmental conditions. So, we need to get some feedback from the real conditions. There are some patterns, which are called drive cycles, in which they come up with different scenarios that you may expect in the real life. But these are not 100% real life conditions. So, there are some sort of modelled or simplified models, basically. And what would be interesting to see is getting data from the customer later, based on the driver’s behaviour and get that data and then feed that into our system to see how our system behaves in such conditions. So, we can get more insight on the characteristics of our system. For example, how our system will be efficient in such conditions. Or we can also learn more deeply how we can design, for example, our motors or our power conversion units.

Cassidy: That’s interesting. So, you take that behavioural research and then apply it to see how the engine reacts? How would you test that?

Mehdi: We can save the comments of the driver. And those comments can be translated on what you want as real conditions. For example, if the driver decides that they want to accelerate, and then they press the pedal for acceleration, then this data will be stored. And then we can use this data as input to our system. So, what we want, basically, is a graph that on the x axis, you have time, and on the y axis, is your speed. So, if we could get this data from the car simulator, which we could, then we have enough information to run our system based on those such data. For example, when you are driving your car in a city, you go with 40 miles per hour for two minutes, and then there's a traffic light, you stop, and then the traffic light goes green, and then you accelerate, maybe rapidly. So, this kind of data, which is basically speed versus time, we can learn about the acceleration. So, we have a speed and time, speed over time gives you acceleration. And then we know, for example, for how long you run your car on certain speeds, etc. So, in the real conditions, you will get many ups and downs because even on a normal road, you're not operating your car with exactly 40 miles per hour, you go 41, 40, 39, etc. And your car, or your electric propulsion unit, should adapt itself based on such small changes.

Cassidy: Data collected on the driver simulator of IM@UCL can be used to understand how drivers drive which will help inform Mehdi’s team of what kind of testing needs to be done in their research. Making their units that much more applicable, efficient, and ready for use. Mehdi also has an idea of what can be done in the future to make IM@UCL’s driving simulator even better.

Mehdi: I've seen the simulator; it is a very nice design. It is very easy to operate and well done to both Bani and Helga for doing it. And it’s not challenging as such, but perhaps we could develop a bit more. For example, if in the future we could provide some sort of feedback from the road to the system - that would be much nicer. For example, you need to put some sort of hydraulic systems as a few motors that somehow simulate the real conditions, which would be quite nice to have. But apart from that, I like the system a lot. It is very versatile and very helpful.

Cassidy: The future of electric vehicles is bright, thanks to the hard work of people like Mehdi and his research team, and access to valuable resources like IM@UCL’s facility. Just think, in a few years’ time, you could be in an electric vehicle that utilises the technology created right here at UCL. 

With our next guest, we will be switching gears from open road to open water.

Yuanchang: My name is Dr. Yuanchang Liu and I’m from Mechanical Engineering. I'm currently the lecturer within the department with the main research about robotics and autonomous systems. And we're specifically working on marine autonomy, including sensing perception, including planning and control.

Cassidy: Yuanchang works on the autonomy of a variety of maritime vessels ranging from small boats that are deployed for search and rescue in post disaster scenarios, to large cargo ships that import and export goods. But regardless of the size of the vessel, there are certain standards that need to be met. For example… 

Yuanchang: …the boat needs to avoid other vessels which are moving to prevent any collisions, and to ensure safety. 

Cassidy: He also needs to…

Yuanchang: …ensure that a boat is able to approach a birth and stop within the birth within certain range.

Cassidy: And…

Yuanchang: …if the boat is given service waypoints, then the boat needs to track these waypoints as accurately as possible.

Cassidy: Making sure that a vessel is able to autonomously avoid other vessels, pull up to a dock successfully, and accurately follow a designated path can be difficult. Especially, when you consider the fact that environmental conditions can have a huge impact on how a vessel is able to manoeuvre around. Speaking of environmental conditions, there is a 4th standard that Yuanchang is always aiming for when creating his vessels: environmentally friendly design.

Yuanchang: The shipping industry has a huge responsibility to address the climate issues. This is because a large proportion of the CO2 emission is actually coming from the shipping industries, and to develop appropriate decarbonisation technologies for ships is crucial.

Cassidy: Creating an environmentally friendly maritime vessel that is also able to navigate through waters accurately despite environmental conditions is a huge challenge. One that is made even more difficult by the logistical problems that come with testing an autonomous maritime vessel.

Yuanchang: You can't simply just build a boat and test it on the lake. To do the test, to think of what kind of research questions will be coming from the actual boat is quite challenging. So that led me to do a lot of background research. And also, we have, in collaboration with a lot of maritime industries, in-depth conversations.

Cassidy: As Yuanchang has pointed out here, when it comes to maritime robotics, you cannot research and test your vessel in a laboratory bubble. You need insight into how maritime industries operate and some of the challenges they face. You have to work in collaboration with maritime industries to gain understanding and be able to come up with research questions. Then, you need a method for testing your design - something that can be quite difficult when designing a ship. But having the right connections can help.

Yuanchang: For example, we had a very good relationship with the University of Plymouth. They had a boat. I think they had the UK’s first educational autonomous vessels platform. So, we collaborated with them and did some tests in oceans. And then during the test, we found out some more challenges or interesting problems. And then we’d go back and do some research. So that's sort of like a loop. We had some knowledge, we tested, and we found new challenges, and we go back to further develop the technologies.

Cassidy: Yeah, it must be a long process then if you're constantly going back and then having to reloop again and again just to see. Because I'm sure there's always things that come up that you just haven't thought of, or I guess also testing at different weather climates during different seasons is probably going to be a little different. 

Yuanchang: I still remember one of the experiments we've done with Plymouth. I think in Roadford Lake, close to Plymouth. If my memory serves me correctly, I think it was during February, quite chilly. And not to mention the cold temperature on the lake. So, the weather was not very good, but we were able to manage it. And yeah, I think it's quite a good memory for us anyway.

Cassidy: Yeah. Were you out on the water for like a really long time outside?

Yuanchang: Our plan was about six hours, but in the end, we couldn’t stand. 

Cassidy: Oh, gosh. And that wind’s always a killer too.

Yuanchang: Yep. And it was raining. 

Cassidy: Oh gosh!

Yuanchang: And a strong wind as well. But if we look at it from the other way, which is that the bad weather creates more challenges to our platforms so we can sort of have a better understanding of the platforms.

Cassidy: Although this type of testing in the water, especially under difficult weather conditions, is great for seeing how well a platform can perform; having a way of testing in a laboratory beforehand could make it more likely that tests in the water will be successful. Thus, reducing the amount of times needed to go back and forth to a body of water. This is where the IM@UCL facility comes into play.

Yuanchang: One of the challenges for my research is that we couldn't have the access to the boat, as much, or as frequently as possible. So, we need to build up a virtual environment by ourselves. And actually, I'm trying to work with Helga, and Bani as well, to sort of create a new maritime virtual environment. So then, we can test our boat, test our algorithms in diverse virtual environments. That essentially, first of all, reduces the cost, yeah? Because running the boat on a lake is costing much higher than driving a car on the road. And so, if we can generate a very good result from the virtual environment, then we can transfer the technology from the simulations onto the real platforms and then further test it. 

Cassidy: Creating maritime simulations requires different considerations than when creating road driving simulations. 

Yuanchang: We are in the sort of starting stage to develop this environment at the moment. Because ultimately although the technologies might be the same, but the environment is different. For the road environment, it includes more elements. For example, within the urban environment, you have buildings, you have pedestrians, you have the traffic lights, you have the road, etcetera. But in maritime environments, the structure is much simpler. Basically, we have the sky, we have the water, we have the obstacles - that's it. The main difference is that on the road, although there are lots of uncertainties, but the environment aspects is less, I will say, less significant if we compare it with the maritime. Because on the oceans, you will be expecting varying currents; winds; rain, different heavy rains for example; and sunlight. So, all the different aspects of the environment will have a huge impact on your vessels. So, to create a virtual environment for that ocean environment is quite challenging. And we do need some help or support or conversations with the people with IM group to understand it better. 

Cassidy: The prospect of having these simulators for maritime research is an exciting one because it brings the maritime industry a step closer to achieving autonomy by making the research for it more feasible and affordable. It’s an aspect that has held the maritime industry back in the past. 

Yuanchang: The autonomy level of ships, no matter what kind of ships - we have large cargo ships, for example, and we have small boats - they are relatively low compared with the self-driving cars or road vehicles. For example, if I drive a Tesla, you can almost achieve the autonomous driving for you and the different new environments or scenarios. But for the boat, or for the vessels, we're still at the early stage. So currently, for the large cargo ships, or large vessels or ships, we still rely on the human operators on board, even if we want to achieve a certain level of automation, we still require the pilots on board to monitor the processes. And then the next step will be to slightly remove the onboard pilots from the ships on to the land-based stations. So, we sort of achieve the remote control. But still we require the human operators to monitor the whole process, but not on the ships, but from the base station. And then if we move on to the further step, that will be autonomous ships, which means that there's no people, either on ships or at base stations. So basically, there are three stages and we're still on the first stage. 

Cassidy: Yeah. And then I guess like someone brought up a point before about people have to learn how that technology works so it takes a while for that. But I guess if you're talking about a maritime thing, it's not as important because, like you had talked about before, there's not as many elements, it's mainly the environment and other things. I mean, you run into other ships and stuff, but not as much as you are when you're driving and people and everything else. So, I imagine that it could, potentially, happen faster than the automated industry. I don’t know, I could be wrong.

Yuanchang: It could be. But as I mentioned, maybe the traffic environment is sort of easier compared with the vehicles. But ships are very large. To make it autonomous or automated, not only do we need to achieve autonomous navigation, but also involves a propulsion system, involves the communication systems, involves a lot more complicated systems. From an engineering perspective, ships are much more complex than a car. 

Cassidy: But the complexity of a ship doesn’t seem to be the biggest hurdle when it comes to making these vessels autonomous. 

Yuanchang: My personal perspective will be that the biggest drive to achieve any new technology will be the government. Let's take the example of electric cars. If we look back, for example, a decade ago, in around 2010, that's the emergence of electric cars. People were not ready for that. But we go, ‘ok, there’s a new type of car – It looks amazing, its performance is much better than the petrol cars or diesel cars’. And then there's huge drive for the government to tackle climate change. So, we need to sort of use electric cars as much as possible. And then we see a burst of the use of electric cars on the road. So that kind of significantly drives this new technology forward. I will say, if the regulator of the government will be more interested in robotics, or AI or self-driving cars, or even autonomous ships, then there'll be huge, huge, huge progress in the future. 

Cassidy: Yeah, absolutely. Because I guess you need that government support for it to get more funding in order to be able to figure out ways to make things more affordable, as well. Because people aren’t going to do things if they can't afford to.

Yuanchang: Affordable. Yep, exactly. Exactly.

Cassidy: And then what difference do you think this research will make to the people that will ultimately be benefiting from it? 

Yuanchang: Imagine the world that ships are driving themselves autonomously - then things just changed. I mean, first of all costs will be reduced, safety will be improved, efficiency will be improved, and we're going to have a better world. That's the huge, huge impact. And I would like to say that another important thing is how we can ensure the decarbonisation, as mentioned before, of ships. Shipping industries contribute a large amount of CO2 emissions, so we need to ensure that we decarbonise them as much as possible to tackle climate change. That’s one of the biggest issues. 

Cassidy: Yes. That's the ideal world, right? Cargo ships that are able to go on their own and be able to do it without creating much of an environmental impact. And that way maybe because they're not as much of an environmental impact and you're not having to have someone constantly there, you can do more passing back and forth as well.

Yuanchang: Yes, exactly.

Although it may seem like this ideal world of autonomous ship driving with reduced carbon impact, increased safety, and increased international trade is something that will be achieved in the distant future, it might happen much sooner than you think. Especially with the strides in technology made by researchers like Yuanchang. 

This is our last episode of IM@UCL: The Podcast. It has been an absolute pleasure to meet the IM research team and put this series together. I have tremendous respect and admiration for Bani and Helge for creating this one of a kind facility. It is clear that it is making such a positive impact on the way academics are able to carry out their research. Not only for those in autonomous automotive engineering, but a variety of other disciplines such as lighting design, human-computer interaction, and the maritime industry. It’s truly incredible. 

Thank you for listening to IM@UCL: The Podcast. If you would like to learn more about the research at IM@UCL, you can check out their website at www.ucl-intelligent-mobility.com and/or subscribe wherever you are listening to this podcast so you can be notified when new episodes come out. This episode was produced and hosted by myself, Cassidy Martin with music from Blue Dot Sessions. It was brought to you by IM@UCL, which is part of UCL PEARL in Dagenham, and supported by UCL Minds, bringing together UCL knowledge, insight and expertise through events, digital content, and activities that are open to everyone. A special thank you to Mehdi and Yuanchang this month for sharing their time, knowledge and insight. I hope you enjoyed listening to this podcast and feel like you learned something new, like I have with everyone I've interviewed in this series. Take care, and I’ll see you around. Cheers!

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