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Taurus: a powerful mix of industry standard and lessons learned through experience

Automotive drivetrain engineers aim to perfect and refine electric drive lines to the point where they operate right at the edge of what is physically possible. This requires simulation models, to act as cost function in the design process or to train reduced order models. These latter models should incorporate all physical loss and performance mechanisms and should be computationally efficient at the same time. Often however, important contributions to efficiency or performance drops are hidden in empirical build factors. These factors can only be quantified too late in the design process, i.e. after testing of the first prototypes.

Based on our experience we developed Taurus, a simulation tool chain that uses industry standard tools, but adds the necessary embedded experience to capture detailed impact from component level, all the way up to the drivetrain level.

Use case: Taurus eliminates the use of build-factors for motor loss prediction

Detailed modelling in Taurus allows to calculate in a computationally efficient way the loss contributions in the motor induced by manufacturing effects and high-frequency operation. This includes degraded material properties at the cutting edges and mechanical pressure for the manufacturing effects. PWM switching induced losses in the magnets, copper, and iron are also calculated. Figure 1 illustrates the delta in amount of losses and their spatial distribution by including these effects. Prior to the calculations, additional material characterizations have been carried out.

Figure 1: ignoring PWM-induced losses and manufacturing effects leads to incorrect loss distribution data.

This spatial loss information is calculated for all operating points and thus allows further detailed analysis utilizing the data in time-based simulations to identify hot spots or to calculate cycle consumption for the full driveline.

Figure 2: Cycle loss breakdown: industry standard tool (build-factors) vs. Taurus (first principles).

The net effect of this increased fidelity on a drive cycle consumption is visible in Figure 2. It compares the loss predictions from an industry standard tool (using build factors) with the first-principles approach from Taurus and shows the correlation with measurements.

Conclusion

With limited additional characterization, a detailed and computationally efficient calculation allows to optimize cycle consumption and avoid local hot spots. By adhering to two main principles: leveraging industry standard tools and including loss mechanisms on a first principles basis, Taurus enables fast driveline R&D support from concept to troubleshooting.

Introducing DRV Solutions

DRV Solutions is an engineering partner for advanced electric drive lines, supporting from concept to validation. We combine motor & power electronics design, full driveline analysis, and system integration expertise in our Taurus Toolkit. This enables us to accelerate your design and troubleshoot performance issues.

How deeptech is already revolutionising EV powertrain engineering

Simon Shepherd, Head of eDrive and Chief Product Officer, Monumo

Deeptech is transforming EV powertrain engineering by introducing new levels of computational freedom, speed, and system integration, allowing companies to achieve levels of performance and cost reduction previously out of reach through existing methods.

Nature-Inspired System Design

Modern engineering increasingly draws inspiration from nature, where efficiency is achieved through adaptation and system-level harmony. EV developers are now using advanced computational tools to explore organic, highly optimised component shapes and system architectures; mirroring, for example, how a tree or a bird’s wing achieves a perfect balance of forces. Unlike natural evolution, which takes millennia, digital tools allow engineers to iterate and converge on superior solutions within weeks, critical for keeping pace with rapidly changing industry and regulatory demands.

Overcoming Conventional Barriers

Classic engineering methods, which adjust just a handful of design parameters, can no longer solve today’s complex powertrain optimisation challenges. Next-generation computational platforms let engineers evaluate vast combinations of component geometries and system parameters – tens of millions, in some cases -far beyond what’s possible with manual approaches or simple brute-force computation. Intelligent automated routines and novel search strategies deliver the breakthroughs needed when conventional software and human time simply cannot scale

Real-World Results at Scale

Breakthrough deeptech platforms – like Monumo’s Anser® Engine – are now enabling EV makers to rapidly generate and assess hundreds of thousands of valid designs for components such as motors and gearboxes.

• In recent projects, 250,000+ viable motor designs were created in just three days, trimming magnet use by more than 8 % and cutting costs by 4 %, saving €15 per vehicle. [1]
• Expanding system optimisation to include additional variables (e.g. stator dimensions, gears, and motor length) produced over 550,000 valid solutions in five days, achieving savings as high as 11 % (€43 per unit), or reducing losses by 12.5 % at no added cost. [2][1]

The Next Frontier

The emergence of “generative design” tools – able to propose promising designs directly – suggests future engineering cycles will be radically compressed, possibly delivering optimal solutions within minutes instead of days. Monumo’s technology roadmap forecasts continued gains as greater systemlevel freedom, parametric control, and digital intelligence are brought to bear:

• Motor-only optimisation: ~5 % cost reduction
• Whole-system integration: 10 %+
• Projected potential with full-system and freeform optimisation: 20 %+ cost reduction.

Deeptech is no longer a future prospect: it is already driving major advances in EV powertrain cost, weight, and performance, for the manufacturers prepared to fully adopt it.

Simon Shepherd is Head of eDrive and Chief Product Officer at Monumo, a deeptech startup based in Cambridge and Coventry, UK, specialising in AI-driven engineering solutions. Ready to explore how deep-tech can transform your powertrain development? Contact Simon.Shepherd@Monumo.com, see more at monumo.com listen to him speak about our latest developments at 11:15 on Wednesday 3rd December in Deep Drive Track L.

AI-Powered Engineering Software for Electric Drives: OPED

Boosting powertrain development with agility, fast time-to-market and optimal product-market fit

Dr. Martin Hofstetter, Head of E-Mobility and Alternative Drivetrains Research Group, Graz University of Technology
Dr. Dominik Lechleitner, Senior Researcher, Graz University of Technology

Designing electric powertrains is challenging: engineers must quickly find competitive designs and optimize the system for multiple key performance indicators (KPIs) at once, e.g., efficiency, cost, and package. The industry-approved engineering software OPED (Optimization of Electric Drives) can do this automatically by combining parametric system models with an AI-based optimization algorithm and exploring hundreds of thousands of design variants within 24 hours.

Development of Electric Drives

The development of electric drives (e-drives) is a highly complex and interdisciplinary process. Engineers must simultaneously design numerous electrical and mechanical subsystems (see Figure 1) that must optimally work together while meeting ambitious system targets for performance, efficiency, cost, and packaging. These objectives are often conflicting – improving one typically worsens another. Moreover, this highly challenging task must be solved under strong time pressure as it is critical for ambitious time-to-market goals. Therefore, engineering of electric drives demands digital tools capable of handling multi-criteria optimization and cross-domain interactions in an integrated way to quickly provide solid answers to complex questions.

Revolutionizing the Development Process with OPED

The software OPED fundamentally changes how e-drives are developed. Instead of relying on sequential design steps and manual iterations, OPED uses parametric system models combined with an AI-powered evolutionary optimization algorithm to explore the full design space automatically. The outline of OPED is shown in Figure 2: Based on specified e-drive system requirements, the design problem is encoded as a multi-objective optimization problem. The intelligent design algorithms then generate different e-drive designs, which are evaluated by system analysis models. Based on the calculated design properties, the optimization algorithm rates the generated designs and aims at improving them based on the best found designs so far. This closed loop of design analysis and synthesis continues until no more improvements are observable and converging behavior is present. Furthermore, self-learning artificial neural networks boost the optimization performance by guiding the optimization algorithm and directing its search towards promising design regions. Within 24 hours of computation time, around 50 design parameters are varied, hundreds of thousands of possible e-drive designs are evaluated, and the most promising ones are identified based on multiple concurrent objectives such as

• performance,
• efficiency,
• cost,
• package integration,
• carbon footprint,

and any other design objective – everything that can be calculated, can be optimized. The result is a Pareto front of optimal solutions, providing engineers and decision makers with a clear overview of achievable trade-offs and design potentials. By merging simulation, optimization, and system understanding in one integrated workflow, OPED enables rapid development cycles. Agility is key: every request for quote (RFQ) or sudden project change request (PCR) is replied with fast and solid answer, tailor-fit to the specific requirements. Taking informed decisions early ultimately leads to an optimal product-market fit for the e-drive system and a fast time-to-market.

Figure 2: From e-drive system requirements to optimal e-drive solutions with OPED

Master Challenging Targets of Package, Efficiency and Cost within 24 Hours

OPED’s strength lies in its versatility. The software can be applied to a wide range of design questions – from component sizing and material selection to system-level trade-offs and product family development. Moreover, as system requirements are often vague and uncertain in the early development stages, OPED can be utilized for requirements engineering. Another powerful capability lies in the full 3D package investigation: OPED not only finds designs that comply with a given 3D target installation space, it also provides possible packaging options within the available space. An example is shown in Figure 3, which depicts two possible design solutions for an e-drive: One with the smallest possible length and one with the smallest possible height (e.g., providing additional trunk space for applications at the rear vehicle axle).

Besides package feasibility, both energy efficiency and cost are always critical and conflicting KPIs. To select the most suitable solution, OPED provides a Pareto front of e-drive designs (Figure 4), where each point represents one optimal design solution. Accordingly, engineers and decision makers are provided with a solid foundation for selecting the most suitable system solution respecting the specific goals of each vehicle application. As each design solution from OPED contains detailed technical information – including a 3D CAD model – a seamless and smooth transition from OPED results to the A-sample development is ensured. This makes OPED a powerful enabler for fast and digital electric powertrain development.

Figure 3: Example of e-drive packaging options; available installation space is shown in blue

Concluding, OPED enables engineers and decision makers to

• respond quickly to requests for quote (RFQs) and project change requests (PCRs),
• solve conflicting KPIs & do requirements engineering,
• develop competitive solutions with product-market fit,
• design optimal product families, utilizing commonality and carry-over-parts.

OPED is established in practical use at a leading global automotive tier 1 supplier – with high potential forscaling across other suppliers and OEMs.

Figure 4: Select the sweet spot of energy efficiency vs. production cost (vehicle model from [1])

Sources:
[1] Holiday, D. (2021). Jaguar I-pace Concept. https://sketchfab.com/3d-models/jaguar-i-pace-concept-3ea106994ec9442eb4b72906026fa215. CC Attribution: https://creative-
commons.org/licenses/by/4.0/, modified. [Online; accessed 13 February 2024

From Lab to Exhaust: A Startup’s Breakthrough in CO2 Transformation

Alicja Stankiewicz, CTO, Coat-It
Marek Turkiewicz, CEO, Coat-It

Pollution kills more people globally each year than war, hunger, or disease. And at the heart of this crisis is carbon dioxide (CO2) – the primary greenhouse gas driving climate change.But what if CO2 could be split and transformed before it ever leaves a tailpipe?

That’s the vision behind RainIons, a U.S.-based startup that has developed a revolutionary powder capable of reducing greenhouse gas emissions – including CO₂, NOx, and hydrocarbons – by transforming them into safe, stable molecules. The application of technology is currently being developed further by COAT-IT, a Polish startup specializing in the engineering of high-temperature-resistant coatings tailored for practical automotive applications.

The Science Behind the Solution

The innovation combines pyroelectric and piezoelectric minerals with naturally occurring radioactive materials (NORM) in a conductive matrix. This unique blend emits alpha particles, negative ions, and electrons – without external power. These particles ionize pollutants and split strong molecular bonds, including those in CO₂.

Independent studies and internal evaluations suggest the solution can significantly reduce CO₂ emissions across a variety of conditions. At elevated temperatures (around 500 °C), reductions have been observed above of 50 %. Even in lower temperature environments (70 – 200 °C), meaningful decreases in CO₂ – typically within a 25 – 30 % range – have been noted, with no harmful byproducts identified. In moisture-rich settings, reductions of up to 50 % indicate that water may play a catalytic role in the
transformation process.

From Tourmaline to Transformation

Inspired by earlier research on tourmaline-infused asphalt, the tourmaline-based “negative ion powder” was infused into a conductive coating and applied it to a diesel muffler. FTIR spectroscopy revealed that CO₂ was being split into graphite and oxygen, with water concentration directly influencing reaction efficiency.

What’s Next?

COAT-IT is now developing durable, high-temperature coatings for commercial deployment. The next phase includes real-world trials using diesel engines and custom exhaust systems. The goal: to quantify transformation products and optimize substrate design for maximum pollution reduction.

If successful, this technology could redefine emissions control – turning exhaust systems into active climate solutions.

Data Driven Cost Measure Generation for Automotive Systems Using Teardown Intelligence and AI

Ivan Jovanovic, Team Leader Incubation InnoHub

Cost optimization in modern drivetrain systems requires more than benchmarking—it demands structured, data driven ideation. This article presents an AI supported methodology that leverages largescale teardown intelligence to systematically generate and assess cost measures at component and system level. The approach bridges the gap between engineering detail and cost strategy decision-making.

Introduction

Automotive drivetrain systems are undergoing rapid transformation driven by electrification, increasing system complexity, and mounting cost pressure. Engineering teams are expected to identify cost reduction opportunities earlier and with greater confidence, while preserving performance, quality, and compliance. Traditional cost

engineering approaches—often based on expert workshops, static benchmarks, or manual analysis—struggle to scale with the growing volume and complexity of available technical data.

This article presents a structured, data driven approach for generating cost measures for systems using largescale teardown intelligence combined with AI supported analysis. The methodology is designed to support engineers and cost analysts in identifying, structuring, and prioritizing cost measures based on factual technical evidence rather than assumptions or isolated examples.

Technical Challenge

Teardown databases today contain thousands of components, materials, manufacturing processes, and architectural design choices across vehicle generations and OEMs. While this data provides a rich foundation for cost insights, extracting actionable cost measures remains challenging due to:

• High data volume and heterogeneity
• Limited traceability between design choices and cost impact
• Dependence on individual expertise to formulate improvement ideas
• Difficulty comparing alternative technical solutions at scale

As drivetrain architectures evolve—especially in electrified powertrains—there is a growing need for systematic methods that transform teardown data into concrete, reusable cost measures.

Methodology

The presented approach is based on three core technical pillars:

1. Structured Teardown Intelligence Componentlevel teardown data is normalized across materials, geometries, manufacturing processes, and system architectures. This enables cross vehicle and cross-generation comparisons within subsystems.
2. Cost Measure Pattern Identification Historical teardown data is analyzed to identify recurring cost relevant design patterns, such as material substitutions, part integration, geometry changes, or process shifts. These patterns are abstracted into reusable cost measure templates that are independent of a single vehicle or OEM.
3. AI Supported Ideation and Filtering An AI based engine combines teardown evidence, cost drivers, and engineering constraints to generate potential cost measures. Measures are contextualized by vehicle segment, drivetrain type, and system boundaries, allowing relevance filtering and prioritization based on feasibility and expected impact.

Concrete Example: Evidence Based Part Elimination

Teardown analysis reveals that the removal of the external brand logo on the hood—first observed on the Tesla Cybertruck and later adopted on recent Model Y versions—constitutes a validated example of part elimination for cost optimization. This decision removes a complete component and associated assembly steps, improving manufacturing efficiency and reducing part count. Such ground truth examples enable data driven challenges to traditional design choices, while highlighting that radical cost measures often require longer internal alignment despite their technical simplicity.

Achieved Innovation

The key innovation lies in shifting cost measure generation from an experience driven activity to a repeatable, data supported process. Instead of manually deriving ideas from individual benchmarks, engineers can explore a structured set of cost measures grounded in real, observed design solutions.

For drivetrain systems, this enables:

• Faster identification of technically realistic cost measures
• Improved transparency between design decisions and cost impact
• Better reuse of historical teardown learnings across projects
• Support for early phase concept and target setting activities

The approach does not replace engineering judgment; rather, it augments it by providing a technically substantiated starting point for cost discussions and design trade-offs.

Conclusion

As drivetrain technologies continue to evolve, cost engineering must evolve in parallel. Leveraging teardown intelligence through structured data models and AI supported ideation offers a scalable way to generate high-quality cost measures rooted in real engineering solutions. This methodology supports more informed, fact-based decisionmaking and helps bridge the gap between technical design and cost strategy in modern automotive development.

Husco Automotive: Engineering Solutions That Move Mobility Forward

Steven Musbach, Account Manager

Husco Automotive is a global engineering and manufacturing partner delivering advanced actuators, valves, and fluid control solutions for automotive applications across internal combustion, hybrid, and electrified vehicle platforms. With decades of systems‑level expertise, Husco collaborates closely with OEMs and Tier 1 integrators to develop production‑ready technologies for driveline, engine, and transmission applications—delivering improved efficiency, durability, and functional performance. As a production partner, Husco offers uniquely engineered solutions across a broad product portfolio, supported by world‑class supplier sourcing and vertical integration advantages.

Husco Automotive’s portfolio includes a range of precision‑engineered solenoids, actuators, and thermal management devices designed to deliver efficient, reliable control across critical automotive applications:

• Ring solenoids engineered for fast response, low power consumption, and robust performance across demanding automotive duty cycles
• Transmission valve sets delivering precise hydraulic control for modern transmission systems where efficiency, repeatability, and reliability are critical
• Motor actuators specifically designed to meet vehicle application requirements, improving system efficiency and overall vehicle performance across conventional and electrified platforms
• Driveline disconnects engineered to smoothly and quietly engage and disengage at the wheel end, axle, transfer case, or differential—reducing efficiency losses while maintaining durability and a seamless driving experience

Learn more about our full product lineup at Husco.com/Automotive.

Husco Automotive’s engineering teams work directly with customers to develop application‑specific solutions that integrate seamlessly within each vehicle system. With deep expertise in electro‑hydraulic and electro‑mechanical design, system modeling, validation, and production readiness, Husco engineers collaborate from early concept through launch—aligning performance, packaging, durability, and manufacturing requirements. This close engineering‑to‑engineering partnership enables Husco to operate

as an extension of the OEM team, accelerating development cycles while delivering solutions optimized for real‑world application demands.

Husco has developed a world class supply chain capable of supporting global, USMCA, and Tier‑N supply models to provide partners with reduced supply chain risk at competitive pricing.

Vertical integration is a core element of Husco’s manufacturing strategy, highlighted by in-house coil winding operations, injection molding capabilities, and dedicated automation design and manufacturing teams. These integrated competencies enable optimized production flows, faster lead times, competitive pricing, and manufacturing strategies uniquely tailored to each program.

Through cutting-edge engineering, a world-class supply chain, and vertically integrated manufacturing, Husco Automotive delivers scalable, production-ready solutions that help customers meet performance, efficiency, regulatory, and supply-chain requirements—while positioning their vehicles for the future of mobility.

Best-in-class Thermal Assessment of Electric Powertrain

Mario Theissl, CEO, Theissl Systems GmbH

THEISSL systems enables precise measurement of temperature and torque in electric drive units with its minimally invasive sensor telemetry technology that is tailored specifically to each customer application. These systems can be seamlessly integrated into existing drive components with minimal need for system modifications, allowing for highly accurate measurements under real-world test bench and vehicle conditions.

With project-specific telemetry units for E-machine rotors gearbox shafts and clutches, the original characteristics of the DUT are inherently preserved while making optimal use of the available installation space. All systems are entirely contactless, transmitting wirelessly to the evaluation unit to ensure reliable performance on high-speed rotating components.

At the core of thermal EDU characterization is the choice of the right sensor elements. Therefore, as a full-service partner, THEISSL systems supports the entire measurement process starting from the definition of test points and the selection of suitable sensors all the way to data analysis after a successful test run.

Even in demanding applications, such as rotor temperature measurements in electric drives, up to 32 thermocouples can be used to gain vast knowledge of the thermal behavior of the DUT. Another variant of our telemetry boards is just 10.5 mm wide, foldable, and bendable around tight radii, which enables temperature measurements on gear teeth and bearing inner rings on transmission shafts. Furthermore, it could be mounted on the rotor shaft, for gearbox input torque measurement e.g. to determine system efficiency.

This measurement technology was implemented in a VW ID.3 demonstrator vehicle, which is showcased at CTI 2025 in Berlin. The system captures inner and outer bearing ring temperatures, gear tooth temperatures, as well as torques at the gearbox input shaft and side shafts. In the E-drive rotor temperature measurement, a telemetry system capturing 16 individual test points was complemented by four additional sensors on the stator windings, giving unprecedented insights into the thermal behavior of the
vehicle’s drive train.

This data, collected over more than 10,000 km of test drives then formed the basis for the training of a Thermal Neural Network (TTN) modelling the thermal behavior of the E-machine. Due to the large number of temperature measurement points, the temperature estimator for the rotor magnets achieved a highly respectable accuracy of ±1.5 K.

Application example: Thermal testing of the electric drive unit of the VW ID.3

A.J. Rose Installs World-Class Equipment in Response to Industry Trends

Electric vehicles are revolutionizing the automotive industry in a way that has not been seen since the seatbelt became mandatory in 1967. Competition among OEMs is increasing and the modern day ‘race to the moon’ is underway, lead by manufacturers such as Volkswagen, Ford, GM and Volvo as they roll-out EV & hyrbid models off the assembly line. Not to be forgotten are more than 100 ambitious startups looking to make a name in the automotive world. Take a couple steps back in the supply chain and there are countless automotive suppliers watching the competition unfold, excited for the new market opportunities this will bring.

Metal stamping companies make up a large part of the automotive suppliers wondering where they will fit into the electric vehicle landscape. Many likely wondering what their new identity will be 10 years from now. It is certain that metal stampings will remain a major part of the automotive supply chain as we transition to EV, but the type of components that will be stamped is the question mark. A reputable stamping supplier that once specialized in powertrain components may soon find their stamping presses being used for battery trays and EV motor laminations. In order to stay agile and be prepared for any type of stamping coming through the pipeline, a supplier needs two things: First, the the willingness and unity to change even if it’s outside their niche, and second, the necessary equipment and processes to support the evolution.

In the case of A.J. Rose Manufacturing Co., they recently invested in new equipment intended to support the markets of the future. That equipment is a newly-built servo press from Aida. This will be the 58th press at A.J. Rose and also the largest press at 1375 tons. At this tonnage, it opens doors to new markets and product lines with the ability to to produce larger parts and run thicker material. They are adapting to the market, not expecting the market to adapt to them. At a bed size of 191” x 70” and a 20 inch stroke, A.J. Rose will offer more capability to their customers looking for large stampings. A purchase of this magnitude was a decision based partly on current necessity and partly on strategic forecasting of future demand. A.J. Rose is positioning themselves to support the increased sourcings in battery plates, battery boxes, battery trays, large brackets and similar housing components that are becoming popular in the EV space. In order to be nimble in these new markets, the press will be capable of running transfer tools or progressive tools, and the servo motor allows for variable speeds and advanced forming capabilites, such as dwelling at the bottom of the stroke. These features make this a Swiss-Army knife of stamping presses, capable of forming metal into unique geometries in a wide range of size and thickness. This is what puts a supplier in a position for growth, making them attractive with an exisiting customer or one brand new.

A wide range of OEM customers turn to A.J. Rose for high-precision, high-quality metal stampings, therefore it is crucial to maintain their reputation as an innovator in the industry. Having such a reputation associated with their brand helps to establish credibility and lends to partnerships with up-and-coming EV startups. Out of many startups gaining momentum in the EV space, it will certainly narrow down to a short list of companies that rise to the top and begin serious competition in the pure EV markets.

A large pit is dug roughly 20 feet into the ground to prepare for the press. Supporting walls are poured from cement within the hole and a connection is made to the existing underground scrap-removal conveyer (right side).

A gantry system is used to support the weight of the press as it is assembled and secured to the foundation.

The press is assembled and secured in the pit. Capacitors are installed in the back.

High-Strength Sinter Parts for Decoupling units in e-Axles

Powder metal technology is well known for products used in the automotive industry. With the shift to electric powertrains, key requirements such as component strength had to be adapted. This has been successfully achieved by developing and implementing new innovative processes to withstand the loads required in electric axles. Powder metal parts such as planetary gears or disconnect systems can even combine these properties with a significantly lower product carbon footprint compared to conventional steel.

The disconnect system

The primary function of an e-axle disconnecting system is to improve the efficiency and performance of battery electric vehicles by automatically decoupling the transmission shaft from the wheels when no power is required from the electric motor. As soon as power is required, the connection is closed again. Various concepts for disconnect units are available on the market, utilizing shifting components such as dog clutches or sliding sleeves to achieve the mechanical disconnecting function.

Figure 4: Examples of Shifting elements for Disconnecting systems in BEVs

The key functions of a disconnecting system are:

• Energy Efficiency: By disconnecting the e-axle when it is not needed (e.g., during highway cruising when only one axle is sufficient), the system reduces power consumption, which in turn can extend the vehicle’s range.
• Performance Optimisation: It allows the vehicle to perform optimally by engaging or disengaging the e-axle according to driving conditions, ensuring that the required power available when needed.
• Component Wear Reduction: Disconnecting the e-axle when not in use can reduce wear and tear on the drivetrain components, resulting in longer component life and lower maintenance costs.
• Driving Dynamics: Improves driving dynamics by providing better traction and stability control. For example, it can disconnect at high speeds to improve fuel efficiency and re-engage at low speeds or off-road conditions to improve traction.
• Temperature Management: Helps manage the thermal load on the powertrain by disconnecting during periods when high performance is not required, preventing overheating and improving component life.

The Powder Metal Process Route – High strength and Energy efficient

The powder metallurgy process is known for its ability to efficiently produce high volume parts with comparatively low energy consumption. The following chart (Fig.2) gives an overview of all possible process steps. Low loaded parts can have a process route that ends directly after sintering, whereas highly loaded parts such as disconnect sleeves require additional operations like sizing or heat treatment.

Figure 5: The Powder Metal Process Overview

High Strength Process Innovation

Powder metal products such as mass balancer or crankshaft gears are known for their high strength, low weight and additional benefit in NVH performance [1,2]. This is achieved by combining a standard part density in the core area (~7,0g/cm³), with a near full density area where the gears are loaded (left, Fig.3). The high-density area can be achieved by rolling or sizing the sintered part. For even higher loaded components such as disconnect systems, the density in the core area of the part needs to be further increased (right, Fig. 6).

This requires two sizing operations: one to achieve a homogeneous core density of >7,4g/cm³ for the core area and a subsequent one for the highly loaded areas with almost full density. To avoid an additional sizing operation and thus save energy (and also cost), a new compacting technology was developed in a research project – “Die-Wall-Lubrication” (DWL).

In general, organic lubricants (e.g. amide waxes, ~0,8 w%) must be added to powder mixes to ensure lubrication between the compacted part, the die-wall and the core rod during ejection of the part. The disadvantage of adding any organic compound is that it also acquires “space” during compaction and thus works against achieving the highest densities – this makes press densities of >7,3g/cm³ infeasible for series production. With the new DWL-concept, the organic content in the mix can be reduced to levels >0,2 w%. Instead of adding to the powder mix, an oil film is applied directly to the pressing tool (see Fig. 7) and densities of ~7,4 g/cm³ can be reached directly after compacting.

The increase in strength as a function of the core density of a sintered part is shown in the graph below. The tooth root strength of sintered gears has been tested for different core densities. It can be seen, that the achievable tooth root strength is strongly influenced by the core density and can reach values of >900MPa (see Fig.8). An optimised heat treatment (dark blue line in Fig.) can further increase the achievable tooth root strength of the sintered gears compared to a standard heat treatment (light blue line in Fig.) by ~200MPa (+30%).

Rolling of Inner Splines

A special feature added for highly loaded disconnect components is to generate the geometric design of the coupling teeth without mechanical processing. Therefor a customised and cost-effective cold rolling process was developed. Through this rolling process, the back taper in the internal toothing of sliding sleeves, that cannot be produced by an axial compacting process and ensures the retention of the form-lock in the closed state of the disconnect system for force transmission, is formed. In

Fig. 9, a cross-sectional view of the back taper area produced by the rolling process after sintering of the components is shown.

The areas of material densification generated by rolling and the resulting reduction in porosity are clearly visible. The density in the densified area is close to 7,8 g/cm³, which allows mechanical properties similar to steel after heat treatment of the component. Another advantage of this process compared to mechanical processing is the associated strength-increasing transition radii that are inherent to this process. This enables the reduction of stress peaks in the application and providing robust solutions in PM.

Energy efficient PM Route

The PM manufacturing process developed for disconnect systems is very short compared to the conventional steel route. This is underlined by the results of a joint project with iron and steel powder supplier Höganas AB. Using the LCA software SPHERA, the PCF (Product Carbon Footprint) of a powder metal disconnect sleeve was compared with the same part produced using a conventional steel process route (Fig. 10).

The results of the PCF calculations given in Fig.11 were obtained by using the following assumptions:

• Steel powder mix PCF of 0,48 kg CO2e per kg material was calculated according to ISO 14067:2018
• Conventional steel (base scenario) for European primary steel of about 1,9 kg CO2e per kg material
• Conventional steel (scenario 3 and 4): 0,3 kgCO2/kg to represent green steel and 0,55 kgCO2/kg represent steel made of recycled material
• Simplifications for PCF on part level: consider are electricity and scrap for the processing steps of both powder metallurgy and conventional routes
• Electricity mix: For the 5 scenarios, different grid mixes were considered to cover the effect of renewable energy impact

It can be seen, that for all scenarios – even using green steel or steel made only from recycled material for the conventional route – the PM route has a significantly lower product carbon footprint. For both manufacturing routes around a third of the contribution is due to the raw material impact, giving PM a big advantage for base scenario as well as scenario 1+2. But even if only recycled steel or green steel is considered as a raw material source for the conventional route, PM still has an advantage due to the comparatively short process route.

Figure 11: PCF of PM route compared to conventional steel incl. different used energy mixes

Summary

Powder metal components can make a significant contribution to the transition to electric powertrains. The PM process has developed new process routes such as Die-Wall-Lubrication and Rolling of Inner splines to meet the higher demands of e-Axles. The strength levels of conventional steel can be matched and combined with the added benefit of a low carbon manufacturing route. This further supports end customers in their efforts to meet their sustainability goals.

Miba Sinter

Miba Sinter is the largest division within the Miba Group and specialises in the development and production of high-precision sintered components. These components are critical to improving the performance and efficiency of applications in the automotive and industrial sectors. Miba Sinter combines extensive knowledge and innovation with advanced powder metal technology to deliver top-quality products to customers worldwide.

Miba Sinter’s product portfolio includes reliable engine components, transmission parts and other sintered products that help reduce emissions and improve fuel efficiency. Thanks to advanced sintering processes, Miba Sinter can produce parts with complex geometries that offer excellent performance and cost efficiency. Sintered products are characterised by economic manufacturability, high material utilisation, low weight and precise production, making them particularly attractive for the requirements of electromobility.