This white paper covers why using Ultra-Wideband (UWB) technology in wireless battery management systems (BMS) communications offers great advantages. In this paper NXP explains the benefits of wireless communications such as higher energy density, easier pack assembly and second life options. It explains how UWB works and its advantages over narrow-band technology in battery pack environments. And finally, it explains NXP’s UWB wireless BMS full solution, its benefits and how it is protocol level compatible with NXP’s wired BMS solution.

Your download is sponsored by NXP.

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Powering the future of mobility requires sophisticated solutions, and NXP’s Power Management Integrated Circuits (PMICs) are at the forefront of enabling software-defined vehicles (SDVs). NXP’s latest innovations enhance efficiency, safety, and design simplicity for automotive manufacturers.

Discover the key benefits of NXP PMICs:

• Power Efficiency: Advanced low power modes to minimize energy consumption.
• Functional Safety: Built-in safety mechanisms meeting ASIL B or D standards.
• Simplified Architecture: Reduce complexity and component count with the ByLink System Power Platform.

Scalable PMIC solutions also support the growing demands of electrification and autonomous driving, paving the way for streamlined designs and faster time-to-market. Explore how this power management technology is driving a greener, smarter future in the automotive world.

Your download is sponsored by NXP.

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The Ansys SimAI cloud-enabled generative artificial intelligence (AI) platform combines the predictive accuracy of Ansys simulation with the speed of generative AI. Because of the software’s versatile underlying neural networks, it can extend to many types of simulation, including structural applications.

This white paper shows how the SimAI cloud-based software applies to highly nonlinear, transient structural simulations, such as automobile crashes, and includes:

• Vehicle kinematics and deformation
• Forces acting upon the vehicle
• How it interacts with its environment
• How understanding the changing and rapid sequence of events helps predict outcomes

These simulations can reduce the potential for occupant injuries and the severity of vehicle damage and help understand the crash’s overall dynamics. Ultimately, this leads to safer automotive design.

Your download is sponsored by Ansys.

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Efficiency drives the automotive industry, with manufacturers constantly looking for ways to reduce production time and costs while improving vehicle quality and repairability. Electrification is ramping up the pressure even further, forcing automotive engineers to walk a tightrope between convention and innovation. This white paper will help you find your balance.

By combining automation, new workflows and new approaches to vehicle design, modular design enables automakers to enhance manufacturability, repairability and serviceability simultaneously. Read Modular Design for Mobility to learn:

• What modular design means for automotive engineering.
• The difference between modular design and traditional design approaches.
• How modular design can benefit electric vehicle engineering.
• Tips for getting started and succeeding with modular design.

Your download is sponsored by Dassault Systèmes.

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“It’s not a matter of if, it’s a matter of when. We just need to scale up the hardware to get there,” head of technical marketing at quantum software company Classiq, Erik Garcell, told Engineering.com.

Let’s take a look at how quantum computing could impact engineering applications from simulation to digital twins.

Quantum computing in automotive and aerospace

Quantum computing promises tantalizing advantages over classical computing: the ability to solve previously untenable problems, to more accurately simulate quantum mechanics, and to operate at mind-boggling speeds. But this promise has yet to be delivered.

“There is no advantage to quantum computers right now,” Garcell said. “But it’s [part of] a digital transformation roadmap.”

As companies ranging from IBM to Google work to develop more capable quantum computers, the industries poised to use them are paying keen attention. Director of quantum algorithm engineering at Nvidia, Elica Kyoseva, told Engineering.com that many organizations are already investing in seeing how greater scale quantum computers could fit into their engineering workflows.

The automotive and aerospace industries are looking to use quantum computing for simulation, materials development, battery research, route optimization and more.

“A very actively researched area is realizing digital twins of complex chemical materials, which have applications in battery design for electric vehicles, or other areas in engineering that require advanced materials,” Kyoseva said.

BMW, Volkswagen and Rolls Royce have already begun testing quantum computing.

BMW conducted a trial with Nvidia to showcase how Nvidia’s cuQuantum SDK could accelerate quantum circuit simulations to improve generative modeling algorithms. So far they are reporting improved training time of quantum generative models. BMW has also worked with Classiq to explore how quantum algorithms could optimize mechatronic systems.

Volkswagen launched a quantum computing research team in 2016. In partnership with quantum providers including D-Wave and Google, Volkswagen has explored several applications of quantum computing in the automotive industry—such as in the paint shop. The team developed a quantum algorithm designed to maximize the efficiency of applying different primer types without slowing the overall assembly process.

“Challenges like these may sound simple, but in some cases would require near-supercomputer levels of power to solve with traditional hardware,” said David Von Dollen, lead data scientist for Volkswagen, in a 2021 company blog post.

Last year Rolls-Royce claimed it had developed “the world’s largest quantum computing circuit for computational fluid dynamics (CFD)” in partnership with Nvidia and Classiq. That circuit could potentially help Rolls-Royce better simulate the performance of its jet engines.

“It’s a matter of getting better, finer, more accurate simulations,” Garcell said.

Quantum digital twins

Digital twins are another engineering application that could receive a quantum boost. The computing paradigm could enable more detail and complexity in these virtual systems. Nvidia is even working on creating digital twins of quantum computers themselves to advance the technology.

“Some problems are fundamentally very hard to solve by classic computers. Examples are creating digital twins of complex material simulations or solving large optimization problems which include risk analysis or routing or other scheduling tasks. This is where we actually feel AI and quantum computing can make a difference,” Kyoseva said.

Garcell agrees that there will be a big focus on materials when quantum tools catch up.

“It’s easier to simulate quantum mechanics on a quantum computer than a classical one. And that deals with materials development,” Garcell said. “How do you come up with higher strength ratio materials? At some point when you’re trying to figure out how to put these materials together you have to worry about simulating the quantum mechanics of it.”

Lowering the quantum barrier

Despite there being some big new problems that quantum can conquer, the average engineer likely won’t have to change their day-to-day workflows. At least, that’s what Nvidia is hoping for.

“It will not be something [engineers] will have to be particularly aware or make a conscious effort to adapt to this new type of computing,” Kyoseva said.

Software should automatically take care of routing computing tasks to the right chip, classical or quantum. Engineers wouldn’t need to be trained in how the chips process the information. They would just see the results.

“Our goal is that this work will transcend to every engineer’s workflow. It will enable them to be more efficient, let’s say to do much higher throughput of calculations and simulations,” Kyoseva said. “But at the same time, this will be done in the background.”

This ease of adoption is what quantum companies are relying on. Companies like Classiq and Nvidia are developing the software frameworks and infrastructure to pair with the hardware when it is ready to go. Once the technology catches up with our computing ambitions, they want you to be ready to pick it up for your simulations without a second thought.

That lower barrier to entry is already looking promising. “We see more and more interest in people coming from different fields and areas being interested in exploring quantum computing for their industry,” Kyoseva said. “For me I just can’t wait until we see the full potential of quantum computing realized and transforming these industries.”

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Rivian and Volkswagen Group (VW) have announced a joint venture to develop next-generation software-defined vehicle (SDV) platforms for their future electric vehicles, with VW investing up to $5 billion, starting with an initial $1 billion. This collaboration aims to leverage Rivian’s advanced electrical architecture and software expertise to create a superior SDV technology platform. The venture will accelerate software development, enhance scalability, and reduce costs for both companies.

Through this partnership, both companies envision launching vehicles equipped with the new technology by the latter half of the decade, and VW will use Rivian’s existing platform in the short term. The joint venture is expected to finalize in the fourth quarter of 2024, pending regulatory approvals.

By pooling their expertise and resources, OEMs can accelerate collaborative return from innovation. Organizations can join forces in multiple ways. For instance, an established OEM can acquire or invest into a niche start-up. This can be achieved through creating a new legal entity like a joint venture (JV), investing into another organization to access given capabilities or capacity, or acquiring a competitor or a supplier to gain access to specific technologies. In this context, PLM strategies play an important role in realizing value from such co-innovation partnerships.

Let’s explore how PLM and ERP facilitate real-time collaboration, design reviews and iterative testing, ensuring swift integration of innovations into production.

How PLM powers collaboration, expansions and acquisitions

Organizations grow through both organic transformations and inorganic expansions. Inorganically, business acquisitions and venture capital investments present growth opportunities through access to new capabilities, markets and technologies. The initial challenges from acquisition are multifold and can be summarized in five key PLM questions:

1. How to leverage or scale one organization’s capabilities to drive value across one another?
2. How to drive synergies across organizations without damaging competitive advantage?
3. How to protect and expand on each organization’s intellectual property (IP)?
4. How to integrate PLM and ERP capabilities across two partner organizations to foster effective collaboration, building on each other’s strengths?
5. How to harmonize and consolidate business capabilities across parent and child entities, or across partnering entities, to remove duplication and address gaps?

Specific answers to these questions will depend on multiple strategic factors, including commercial agreements between companies. It’s also a matter of defining the relevant strategy to enable cross-organizational collaboration, drive business integration, leverage best practices across organizations, consolidate enterprise capabilities and ultimately seek simplification.

The first PLM capabilities to consolidate typically relate to core product and project data: from BOMs, materials, software, xCAD, quality standards, compliance requirements, business processes, supply chain integration—aligning processes and associated systems of record/engagement repository. Initial steps towards building a common PLM backbone often relate to data exchange alignment based on common formats and processes. Other the other side, ERP foundation includes aligning procurement, product costing, compliance, sustainability, financial and other core enterprise requirements.

How PLM fosters portfolio alignment and data protection

Partnering across organizations seeking to co-innovate implies a robust commercial alignment to capitalize on respective investments and related business commitments. Such partnership is often characterized by driving product portfolio synergies, sharing resources and value assets, sharing benefits and return on investments.

Business acquisitions and associated investments translate in five strategic perspectives:

• Market expansion: Acquiring businesses to expand into new markets or geographical areas to gain a competitive edge.
• Product diversification: Investing in acquisitions to diversify the product portfolio—including adding new product lines, enhancing existing products, co-developing new variants or product lines, or integrating complementary products to meet broader customer needs.
• Technology advancement: Acquiring businesses to gain access to new technologies, IP, or technical expertise—staying at the forefront of innovation and maintaining a competitive advantage in the market.
• Operational synergies: Focusing on acquisitions that offer operational efficiencies and cost savings—streamlining processes, achieving economies of scale, reducing redundancies and improving overall operational effectiveness.
• Strategic partnerships and alliances: Forming strategic partnerships or alliances through acquisitions to strengthen the company’s position in the industry—enhancing collaboration, share resources and drive mutual growth.

In PLM terms, this translates to integration of new market requirements and regulatory standards into the product development process. It involves managing a range of products and variations within a PLM ecosystem with broader access control to ensure cohesive lifecycle management. From a technical standpoint, stronger collaboration requires updating and integrating new technologies and knowledge into existing PLM frameworks to support innovation and product enhancement. Furthermore, it entails harmonizing processes and systems across merged entities to streamline operations and reduce PLM-related costs.

How PLM strategies support mergers and acquisitions

PLM strategies play a critical role in supporting business acquisitions by providing a structured framework for integrating and managing the combined entities’ product development processes. PLM value drivers contribute to business mergers and acquisitions in multiple ways:

1. Unified product data management: PLM systems consolidate product data from both acquiring and acquired companies, ensuring consistency and accessibility. This unified approach reduces data silos and enhances collaboration across teams.
2. Streamlined product development: By integrating the product development processes of both organizations, PLM strategies ensure that best practices are shared and adopted, leading to more efficient and innovative product development cycles.
3. Enhanced compliance and quality control: PLM processes help manage compliance with industry standards and regulations by maintaining comprehensive records of materials, processes, and product specifications. This ensures that all products meet quality and regulatory requirements.
4. Efficient change management: PLM strategies facilitate effective change management by providing tools to track and manage changes in product design, development, and production. This helps in quickly addressing any issues that arise during the integration process.
5. Improved resource utilization: PLM processes enable better resource planning and utilization by providing visibility into the capabilities and capacities of both organizations. This leads to optimized use of resources and improved operational efficiency.
6. Accelerated time-to-market: By harmonizing processes and leveraging system synergies, PLM strategies can significantly reduce the time required to bring new products to market. This is crucial for maintaining a competitive edge in fast-paced industries.
7. Innovation and IP protection: PLM systems ensure that intellectual assets from both organizations is protected and leveraged effectively, from products to data assets, processes, resources, etc. First and foremost, this fosters innovation by providing a secure environment for collaboration and knowledge sharing.
8. Scalable and flexible integration: PLM strategies provide scalable and flexible integration frameworks that can adapt to the evolving needs of the business. This ensures that the integration process is smooth and can accommodate future growth and changes.

By implementing robust PLM strategies, organizations can effectively manage the complexities of business acquisitions, driving value creation, innovation, and long-term success. This involves continuous simplification and consolidation, balancing control and flexibility to ensure cohesive operations while maintaining agility to respond to market changes and new opportunities.

Consultants often debate the challenges of PLM and ERP implementations as they are complex by nature, but these changes present opportunities to learn and break the status quo. This is especially crucial for companies serving multiple customers through hybrid PLM ecosystems or those aiming to enable mergers and acquisitions by building modular, “plug-and-play” processes, data flows and systems.

Robust PLM strategies align product development processes, leveraging the combined strengths of acquiring and acquired companies to unlock new value streams, enhance productivity, and reduce time-to-market. They provide a collaborative platform fostering continuous improvement and creativity, while ensuring access to a unified knowledge base and shared IP. Effective data management, compliance adherence, and quality control within PLM frameworks lay a strong foundation for sustainable growth, maintaining high product quality and meeting regulatory requirements.

The post PLM and ERP foundations to successful mergers, acquisitions, JVs appeared first on Engineering.com.

The success of a global transition to electric vehicles (EVs) depends on organizations that research and develop electric motors, alternative fuel supply, components, and charging solutions.

In this eBook, you will learn how car manufacturers and industry suppliers alike are using modeling and simulation as part of their R&D and design process.

Topics include:

• Rotors for electric drives
• Flexible wireless charging systems
• Hydrogen fuel cell development
• Power magnetic devices
• Three-phase inverters and DC link capacitors

Your download is sponsored by COMSOL.

*Please see www.comsol.com/privacy for COMSOL’s Privacy Policy. Contact COMSOL at www.comsol.com/contact for more information. Note that COMSOL will follow up with all registrants about this eBook and any related questions.

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Tesla warned to fix factory air quality violations

The Bay Area Air Quality Management District’s independent Hearing Board has ordered Tesla to correct air quality violations at its electric vehicle manufacturing facility in Fremont, Calif. A written order is expected to be issued this week to compel Tesla to stop frequent and ongoing violations from the paint shop operations at the facility. The agency accuses Tesla of emitting harmful precursor organic compounds and toxic air contaminants directly into the atmosphere without proper abatement, resulting in 112 Notices of Violation since 2019. In a press release, the agency says Tesla’s recurring violations result from a variety of causes, including Tesla’s thermal oxidizer or related components of the abatement system breaking down, causing emissions to automatically be vented directly into the atmosphere without proper abatement. The agency also says Tesla shuts the abatement system down when there are problems with other equipment in the paint shops.  

Verisurf, Scantech team up

Verisurf Software, Inc. and Scantech Digital, Inc. have partnered to combine Verisurf’s model-based inspection, measurement and reverse engineering software with Scantech’s 3D scanners and optical trackers. The result is single-source consultation, quoting, transactional support and relationship management for complete inspection and reverse engineering solutions. Verisurf’s measurement software is built on a full-featured 3D CAD/CAM platform committed to intelligent Model-Based Definition (MBD) to enable metrology workflows in a seamless CAD environment and maintain model-based digital continuity. These application suites will be bundled with each Scantech 3D scanner or optical tracker for scan data analysis for inspection and quality reporting, mesh-to-surface and solid modeling for reverse engineering workflows.

Simsol joins Siemens Xcelerator

UK-based digital twin technology firm Simsol has joined Siemens’ Xcelerator, an open digital business platform designed to speed up the digital transformation of industry. Manufacturers will now be able to access Simsol services from the global Siemens Xcelerator marketplace. Simsol provides digital twin solutions based on Siemens Plant Simuation and Process Simulate software to simulate factory automation to integrate robotics, control, motion and safety for automated and human operators.

JCB breaks ground in San Antonio

JCB has begun work on a new $500-million factory in San Antonio, Texas, the biggest investment in the company’s history. Work on the 720,000 sq. ft. factory is now under way on the 400-acre site. It will be the company’s second largest plant, rivalled only by JCB’s world headquarters in Rocester, Staffordshire, England, and create 1,500 new jobs over five years. The factory will make Loadall telescopic handlers and aerial access equipment, with production scheduled to start in 2026. The factory will also have the capacity to expand and build other products in the future. JCB employs 19,000 people globally and has 22 factories around the world.

Ansys adds Makersite to Granta

Makersite, a German product lifecycle intelligence software developer, has announced a strategic partnership with engineering simulation software company Ansys to integrate Makersite’s AI-powered solution with Ansys’ Granta software. Makersite’s platform combines AI with data from more than 140 material, process, and supplier databases to help designers understand the impact of materials and process choices in the design phase. Makersite’s material databases and Ansys’ Granta software will simulate various product iterations and scenarios without ever having to build a product in practice.

Mitsubishi Electric nabs Guinness World Record

Tokyo-based Mitsubishi Electric Corp. has been awarded a Guiness World Record title for the fastest robot to solve a rotating puzzle cube (commonly known as a Rubik’s Cube).  The Mitsubishi team used its TOKUI Fast Accurate Synchronized motion Testing Robot (Tokufastbot) to beat the previous record of 0.38 seconds with a time of 0.305 seconds. Mitsubishi says the achievement demonstrates the technical capabilities of the motors, power semiconductors and related technology developed and manufactured by its Component Production Engineering Center. The Tokufastbot performs a 90-degree rotation time of 0.009 seconds thanks to the rotation mechanism built by Mitsubishi Electric’s compact, high-power, signal-responsive servomotors and a color-recognition algorithm developed with proprietary AI technology. The high-speed signal connection and inter-device control are achieved by servomotors as well as a PLC, industrial PC, touch panel display and cameras.

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Jaguar Land Rover (JLR) was acquired by Tata Motors Ltd. (TMC) in 2008 for about US$1.5 billion (£1.15 billion). Following a two-year separation process from Ford Motor Co. (FMC), initiated its new Product Lifecycle Management (PLM) journey in partnership with Dassault Systèmes. The initial vision was for a full scope transition from a very disparate ecosystem inherited from Ford and previous mergers to an integrated PLM architecture with 3DExperience at its foundation.

Perhaps independently of its PLM strategy, JLR reported strong results in the previous financial year. As of end-March 2024, JLR declared record Q4 and FY2024 revenue of $9.9 billion (£7.9 billion) and $36.6 billion (£29.0 billion) respectively, with profit before tax of $836 million (£661 million) and $2.7 billion (£2.2 billion) for the same periods—the highest since 2015.

Building a credible, holistic PLM strategy and associated implementation roadmap from the ground-up is no easy task. It often translates to multi-year business transformations that must be championed at the board level. For JLR, it has been a 15-year journey in the making. It initiated with a greenfield vision in 2010 which gradually evolved into a hybrid bluefield approach to mitigate transition risks while addressing technical readiness and adoption gaps. A bluefield approach implies combining greenfield and brownfield elements.

Contextualizing it to the JLR story, this post discusses why solving complex PLM challenges requires Agile-based problem solving, adaptive change management and realistic strategic realignment to cope with unpredictability and uncertainty.

Reality check: from greenfield to bluefield

Greenfield PLM implementation strategies often initiate from bold/unconstrained ideas, sometimes combined with unqualified wishful thinking and the need for speed (e.g., unrealistically fast deployment ambitions). When left unvalidated, this approach adds challenges in successfully completing digital transformations—particularly in the context of PLM and other enterprise solutions which carry high-level of ambiguity. Such challenges typically relate to a mix of 5 characteristics:

1. Unrealistic expectations: overestimated benefits and underestimated complexity often fueled by senior leadership’s lack of appreciation and ownership of the PLM scope.
2. Inadequate planning and preparation: amplified by insufficient analysis and the lack of a detailed roadmap due to various technical and business unknowns.
3. Unexpected resistance to change: underestimating organizational ability to embrace change, underestimating communication and training needs.
4. Resource misallocation: budget overruns and inadequate skillsets, assuming existing experts can handle new technologies without external hiring or upskilling.
5. Neglecting delivery risk management: failure to monitor and adjust—wrongly assuming the initial plan will work perfectly without the need for ongoing real-time adjustments based on feedback and evolving circumstances.

JLR’s initial PLM strategy was crafted in 2010; it candidly aimed at a perfect alignment, seeking to connect all enterprise capabilities together following a series of greenfield solution deployments. It later realigned its strategy to refocus on an integrated engineering/development toolset—the product data management backbone of innovation—with BOM, CAD, CAE and virtual twins management at its core.

Legacy coexistence and technical debt

Transitioning from the Ford legacy PLM ecosystem was certainly a significant endeavor for JLR. Similar to Volvo Cars, JLR faced several knowledge gaps in managing the complexity and technical debt it inherited from its previous parent company. With hundreds of tools and customized systems, the integration and data migration landscape required selective dual-track solution development and concurrent support to facilitate the transition. The situation was amplified by different practices and core data sets used across two distinct brands, Jaguar and Land Rover.

Progress was at last reported in 2019, by John Kitchingman, who at the time lead EuroNorth at Dassault Systèmes: “Just over 10 years after the project was initiated, the company has finally rolled out a first solution that covers an entire vehicle program: the Defender model. There is still a way to go, but the good news is that this rollout finally happened.” The hard reality is that it took JLR more than twice the time it initially planned to finally roll out a first solution of 3DExperience that covered an entire vehicle program. The journey with Dassault Systèmes continues as JLR now seeks to complete the deployment of 3DExperience across all vehicle programs worldwide. Only then, JLR would be able to initiate the decommissioning of the remaining components of its redundant Ford-based legacy systems.

There is clearly no single quick fix, silver bullet or magic wand that can address all challenges associated with heavily customized and poorly integrated PLM legacy. Limiting old-new solution coexistence and minimizing customization are typical objectives of every PLM initiative. The last mile of JLR’s PLM transformation will consist of scaling its 3DExperience adoption across the entire product portfolio, finally closing the door on years of functional transition and data migration. Subsequently, this will open the door to further opportunities for enterprise capability improvements.

Leveraging digital twins

JLR clearly aims at end-to-end collaboration around its PLM backbone, reaching cross-functionally beyond design and concurrent engineering supply chains. JLR said that “More than 18,000 users across all JLR business areas and suppliers will make use of virtual twins to increase efficiency, improve production management, save time and reduce waste and costs.”

Laurence Montanari, Vice President, Transportation & Mobility Industry, Dassault Systèmes, remains optimistic about hitting the next significant milestone in this 15-year transformation journey: “JLR is utilizing the 3DExperience platform to enhance its virtual twin experience, creating software-defined vehicles that seamlessly integrate both hardware and software development. […] After five years of partnership, we are opening a new era of collaboration beyond engineering and manufacturing through a trusted partnership, where teams from JLR and Dassault Systèmes work closely in short iterations to address JLR and its ecosystem’s challenges.”

The post How Jaguar Land Rover handled 5 major PLM challenges appeared first on Engineering.com.

Sales growth in electric vehicles, led by Tesla and BYD has long suggested the end of gasoline and diesel fuel in the transportation sector. While fuel cells are a viable clean option, lower costs in battery production have made pure electric vehicles the sales leader in green transportation.

But can the momentum of early adopters be maintained? Market surveys suggest that EV sales growth is flattening, as MSRP’s and a lack of public charging infrastructure dampen demand.

* * *
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