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Drive System Design presents design methodology for accommodating future uncertainty in EV powertrain design: ePOP

UK-based automotive engineering specialist Drive System Design (DSD) will present a system-level approach for EV powertrain design in a paper at the 17th CTI China Symposium in Shanghai from 23-25 September. The paper will illustrate how, using the method developed at DSD, future EV powertrains can be better optimized and protected against uncertain global trends in technology development and commodity prices.

While the emphasis for first generation EVs was on shortest time-to-market in response to global emissions concerns, future generations of vehicle will have additional priorities. The foundations upon which these vehicle platforms are based must provide robust commercial viability for the OEMs, regardless of fluctuations in commodity prices such as rare earth magnets, or any re-ordering of the dominance of particular motor or inverter technologies. Our system approach to the design of EV powertrains helps to future-proof them against the uncertainties that lie ahead.

—Lee Sykes, Commercial Director, DSD

The paper, entitled Costly Decisions – creating product strategies robust to market instability and cost volatility, outlines DSD’s Electrified Powertrain Optimization Process, ePOP, and how it has been applied not only to optimize architecture selection but product electrification strategy as a whole.


It evaluates potential material cost fluctuations such as magnet cost instability and the impact of alternative cost trajectories for batteries and inverter technologies.

Author of the paper, Dr Michael Bryant, Principal Engineer, DSD, believes the key enabler within the process is the characterization of subsystem and component design, allowing the process to build complete powertrain variants for simulation.

ePOP rapidly generates the necessary input data—masses, efficiency maps, etc—for each electric powertrain subsystem, for a range of topologies and layouts. The speedy generation of input data permits the simulation of a large number of powertrain combinations, up to several thousand alternatives in one example.

—Michael Bryant

The detail within each of the powertrain variants generated allows intelligent cost functions to be used alongside performance and energy consumption comparisons, enabling studies that not only optimise products, but also determine those electrification strategies most robust against potential cost instabilities and the resulting market scenarios.

The ePOP process utilized for the paper was developed by DSD, in part during the ACeDrive APC grant-funded programme, a collaboration between DSD, GKN and the University of Nottingham to create a next generation eDrive. The core of the project is to develop an integrated high-speed motor/inverter/gearbox, that will be significantly more power dense, efficient and less costly than any comparable system available.


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