Our computational platform designs optimal e-motors and thruster without human intervention. It is used by market leaders in automotive, aerospace, HVACs and electronics (among others) to unveil large sources of optimization for their machines, present in nature, but that have never been exploited by engineers before.
To go beyond engineer creativeness, our codes explore the possibilities of topologies extensively, mesh by mesh. Unnecessary matter is removed. The remaining is disposed to maximize efficiency of the device, providing more performance with less materials and less electricity consumption.
The designs we produce require no additive manufacturing. Simply, they are manufacturable on current tooling, using known and controlled processes.
System constraints enter the design of topologies, making motors equal contributors to other components (controllers, inverters, sensors, …) in search of optimal system performance.
Because nature is optimal and frugal, we help you define your Optimal Target, the best specification available in nature given your set of constraints.
We provide a large range of industries with three cumulative returns :
Return on Investment
We enable short term savings on current operations.
Return on Innovation
We design the next generation of electric motors.
Return on Impact
Our designs have minimal impact on resources and climate.
Compared to state-of-the-art “flux barrier” topology, our own (patented) SynRM prototype offers the following benefits :
In the graph below, state-of-the art SynRM (“Flux Barrier”) performance is plotted in order to determine two points of evaluation, corresponding to two performance objectives traditionally set for a SynRM machine. H1 corresponds to the operating point where torque variation is minimal, at the expense of torque maximization. H2 corresponds to the operating point where torque is maximal, at the expense of torque variation minimization.
In both contexts, Deeper Pulse’s proprietary SynRM delivers significantly higher torque and less torque variation than Flux Barrier SynRM (with no degradation on other metrics, such as heat for example).
At minimum torque ripple (H1) :
DP’s torque ripple is 15% vs. 40% for flux barrier (-xx%)
DP’s torque is 3,75 NM vs. 2,9 NM for flux barrier (+ yy %)
At maximum torque delivery (H2):
DP’s torque ripple is 35% vs. 48% for flux barrier (-xx%)
DP’s torque is 4,05 NM vs. 3,36 NM for flux barrier (+ yy %)
Rigorously compared to state-of-the-art “PM” topology, DP’S own permanent magnet topology offers the following benefits :
Without the need for plasmic modeling, our algorithms rip off useless material while optimizing EM performance of HET topologies. Our manufacturable HET thrusters produce higher performances in the range of the following metrics:
Net specific impulse
Material mass and cost
Billions of us rely on motors to keep life going. Motors are the heart of the world, consuming half of its electricity — but they beat inefficiently. By increasing performance of all motors, big and small, we want to have a major impact on the planet. We collaborate with industrials to deliver greater efficiency, reduce materials and energy use, and eventually protect our natural resources for the next generations.
We believe large deposits of EM efficiency persist in nature, that have never been exploited before. Algorithms let engineers access them to design new types of electromagnetic machines, much cleaner, more efficient and less energy consuming.
We help clients identify these natural deposits, model them, and use them to design the next generation of e-motors and thrusters.
After ten years of academic research, a leading engine manufacturer asks us to reduce the mass of a Hall Effect satellite thruster by 20%. Our solution provides a 75% mass reduction.
We extend the scope of our technology to motors, i.e., any device using a rotor and a stator. We developed and patented our own revolutionary SynRM topology.
Our platform generates electric motor & thruster topologies that outperform greatly the best current machines and are fabricable in large series using existing processes.
Experienced entrepreneur (4 companies created), graduate of HEC and Harvard Business School. Thomas BAUDIN has joined the project to structure the vision and strategy, and his main commitment will be business development.
Youness RTIMI, PhD, graduated from ENSEEIHT in Toulouse. He is the inventor of the technology, having brought it to maturity following ten years of research initiated by Frédéric Messine.
Arnaud BENHAMOU is a graduate from Paul Sabatier University and of the Institut National Polytechnique de Toulouse. He spent 20 years spent in various positions of responsibility in industry. (Automotive, Aerospace and Medical Devices).
Frédéric MESSINE is a university professor of applied mathematics at ENSEEIHT-Toulouse INP. He specializes in optimization, notably for the design of electromechanical actuators and satellite thrusters.