Home Projects Multi Disciplinary Support for a Cambridge Start-Up

The Challenge

Monumo is looking to revolutionise the global electric vehicle market.

Combining deep technology and real-world electric motor design expertise, this Cambridge-based start-up have a mission to create and license next generation electric motor designs. In order to create these faster and better than any other company in the world, Monumo needed to create a combination of simulation, machine learning, artificial intelligence and motor design expertise. When the company was first created it lacked the engineering resource and the business support it needed to get going.

The Approach​

Monumo was originally incubated by our Plextek founders, including Ian Murphy who is now their President. From our large owned-offices near Cambridge, we were able to provide electronics support in addition to business strategy, innovation and technology development consultancy. Plextek have a lot of experience in electromagnetic modelling, key in the development of electric motor designs. We were therefore placed-well to help guide the direction of travel in the early stages of this programme and then to implement components as the work unfolds. The Monumo and Plextek teams worked intensively for a year to rapidly produce results.

The Outcome

We are proud to have assisted Monumo in their foundational stages. They now have their own offices in Cambridge and Coventry, have successfully raised just over £10 million seed capital, and will be raising further capital to scale the business as it continues to grow.

Contact Plextek | Employees check their contact emails on a tablet

Got a project in mind?

Let’s talk

If you have got a project to discuss, or even just an idea, let's talk


Related Technical Papers

View All
an image of our technical paper
mmWave Imaging Radar

Camera systems are in widespread use as sensors that provide information about the surrounding environment. But this can struggle with image interpretation in complex scenarios. In contrast, mmWave radar technology offers a more straightforward view of the geometry and motion of objects, making it valuable for applications like autonomous vehicles, where radar aids in mapping surroundings and detecting obstacles. Radar’s ability to provide direct 3D location data and motion detection through Doppler effects is advantageous, though traditionally expensive and bulky. Advances in SiGe device integration are producing more compact and cost-effective radar solutions. Plextek aims to develop mm-wave radar prototypes that balance cost, size, weight, power, and real-time data processing for diverse applications, including autonomous vehicles, human-computer interfaces, transport systems, and building security.

an image of our technical paper
Low Cost Millimeter Wave Radio frequency Sensors

This paper presents a range of novel low-cost millimeter-wave radio-frequency sensors that have been developed using the latest advances in commercially available electronic chip-sets. The recent emergence of low-cost, single chip silicon germanium transceiver modules combined with license exempt usage bands is creating a new area in which sensors can be developed. Three example systems using this technology are discussed, including: gas spectroscopy at stand off distances, non-invasive dielectric material characterization and high performance micro radar.

an image of our technical paper
60 GHz F-Scan SIW Meanderline Antenna for Radar Applications

This paper describes the design and characterization of a frequency-scanning meanderline antenna for operation at 60 GHz. The design incorporates SIW techniques and slot radiating elements. The amplitude profile across the antenna aperture has been weighted to reduce sidelobe levels, which makes the design attractive for radar applications. Measured performance agrees with simulations, and the achieved beam profile and sidelobe levels are better than previously documented frequency-scanning designs at V and W bands.

an image of our technical paper
Ku-Band Low-Sidelobe Waveguide Array

The design of a 16-element waveguide array employing radiating T-junctions that operates in the Ku band is described. Amplitude weighting results in low elevation sidelobe levels, while impedance matching provides a satisfactory VSWR, that are both achieved over a wide bandwidth (15.7-17.2 GHz). Simulation and measurement results, that agree very well, are presented. The design forms part of a 16 x 40 element waveguide array that achieves high gain and narrow beamwidths for use in an electronic-scanning radar system.

an image of our technical paper
Non-Invasive Auditory Sensing with Affordable Headphones

This paper presents a sensor for measuring auditory brainstem responses to help diagnose hearing problems away from specialist clinical settings using non-invasive electrodes and commercially available headphones. The challenge of reliably measuring low level electronic signals in the presence of significant noise is addressed via a precision analog processing circuit which includes a novel impedance measurement approach to verify good electrode contact. Results are presented showing that the new sensor was able to reliably sense auditory brainstem responses using noninvasive electrodes, even at lower stimuli levels.

an image of our technical paper
GPU Computing

Power limits restrict CPU speeds, but GPUs offer a solution for faster computing. Initially designed for graphics, GPUs now handle general computing, thanks to advancements by NVIDIA, AMD, and Intel. With hundreds of cores, GPUs significantly outperform CPUs in parallel processing tasks. Modern supercomputers, like Titan, utilize thousands of GPU cores for immense speed. NVIDIA’s CUDA platform simplifies GPU programming, making it accessible for parallel tasks. While GPUs excel in parallelizable problems, they can be limited by data transfer rates and algorithm design. NVIDIA’s Tesla GPUs provide high performance in both single and double precision calculations. Additionally, embedded GPUs like the NVIDIA Jetson TX2 deliver powerful, low-power computing for specialized applications. Overall, GPUs offer superior speed and efficiency for parallel tasks compared to CPUs.