Dassault Systemes’ Ravikiran Pothukuchi on SDVs, Virtual Twins and the Future of Automotive Development

India's automotive industry is moving rapidly from conventional ICE vehicles towards EVs, software-defined vehicles (SDVs), connected technologies and AI. The transformation is also changing how vehicles are designed, simulated, validated and manufactured. In an interaction with Ravikiran Pothukuchi, Director at Dassault Systèmes discussed the growing importance of digital engineering, the role of AI in vehicle development, the evolution of virtual twins, hardware-software interoperability, EV simulation and the challenges of bringing advanced technologies to India's vast supplier ecosystem.

Q. India’s automotive industry is undergoing a major transformation with EVs, software-defined vehicles, connected technologies and AI. From Dassault Systèmes’ perspective, what is the biggest technological gap Indian automakers need to address today?

With vehicles evolving from internal combustion engine (ICE) platforms to EVs and now software-defined vehicles, the orchestration between hardware and software has become increasingly important. Vehicle development, which was once largely mechanical, has become a multidisciplinary process involving mechanical engineering, electronics, software and several other technologies.

The challenge is that these disciplines can still be developed in silos. One team may work on the mechanical architecture while another works on electronics and software. When these systems are integrated later, problems can emerge, and fixing them downstream can be costly in terms of time and resources.

The industry therefore needs a common digital backbone that can bring these development streams together. When the vehicle reaches the market, all its systems have to work together, so they also need to be developed and validated together.

Digital technologies enable this multidisciplinary approach by allowing mechanical, electronic and software systems to be modelled as interconnected systems and validated virtually. This is where a common digital platform becomes important.

Mahindra & Mahindra is an example of this approach. The company has standardised most of its design operations on the Dassault Systèmes 3DEXPERIENCE platform, using it as a digital backbone for its new product development process across disciplines.

Q. AI is increasingly being integrated into automotive product development. Are we moving towards a point where AI will not just assist engineers but actually participate in vehicle design, simulation and optimisation?

The automotive industry is under pressure to reduce product development timelines because consumer preferences are changing rapidly. Manufacturers need to bring new variants, models and features to market faster, which means development cycles need to move towards 12 to 18 months. One way to achieve this is by identifying processes that can be parallelised. Design and validation, for example, do not necessarily have to happen sequentially.

That is where MODSIM, which brings modelling and simulation together, becomes important. Traditionally, a design would be handed over to validation engineers, who would test it for crashworthiness, durability, vibroacoustics, fluid dynamics and other parameters. If it failed, it would go back to the design team, creating a time-consuming feedback loop.

MODSIM brings modelling and simulation together so that validation can happen much earlier in the development process. This is what we call 'left shifting'—bringing validation into the design phase. Some companies have been able to reduce vehicle development timelines by several months through this approach.

The next step is automation through AI agents. We have agents such as Leo for engineering, Mary for scientific applications and Ora for business analysis. They can take on specific tasks within the development process. For example, if a simulation shows that an A-pillar or bracket does not meet the required strength, an AI agent can explore alternative materials, geometries or reinforcement strategies. The engineer can then review those options and make the final decision.

So MODSIM integrates modelling and simulation, while agentic AI can automate many of the tasks within that process. The objective is to leave critical decisions with engineers while allowing AI to handle repetitive and computationally intensive tasks.

Q. “Digital twin" has become a common industry term. What does a truly comprehensive digital twin of a vehicle look like?

Digital twins have evolved from being simple geometrical representations to models that can also replicate the behaviour of a physical product. A virtual twin therefore combines geometry and behaviour. It can represent not only what a product looks like, but also how it operates. The concept can also extend beyond the vehicle itself. An automotive company has engineering, manufacturing, supply chain and industrialisation teams, each with their own processes and workflows. These can also be modelled through what we describe as a virtual twin of an organisation.

The next step is modelling how the product reaches the market—how it is manufactured, distributed and sold. This creates a virtual twin of the business or operational model. Together, virtual twins of the product, organisation and business operations can create a virtual twin of the enterprise. This can be useful when companies need to respond to changing business conditions. For instance, if tariffs change and affect a company's sourcing or export economics, a virtual model of its operations can help evaluate alternative sourcing locations, manufacturing strategies or distribution models. AI agents can then analyse these scenarios and identify potential options much faster than traditional manual analysis.

Q. With software-defined vehicles becoming increasingly important, does Dassault Systèmes see the vehicle itself becoming less of a hardware product and more of a continuously evolving digital product?

Software is becoming increasingly important in vehicles, particularly with the emergence of software-defined architectures. Over-the-air updates can modify functions such as battery management, thermal management and infotainment without requiring a physical change to the vehicle. However, this does not make hardware less important. The vehicle still depends on its body, chassis, suspension, steering, braking and other physical systems.

What is changing is the relationship between hardware and software. Software is increasingly responsible for controlling and optimising hardware, making their integration critical. The frequency of updates is also changing. Earlier, major vehicle updates could take months or years, whereas software-defined vehicles can receive updates much more frequently. This creates another challenge: compatibility. A new software update may not necessarily be compatible with an older hardware architecture, such as a previous-generation battery system.

Therefore, hardware and software need to be developed and validated together, with interoperability becoming a critical part of vehicle development. A common digital backbone can help manufacturers validate the hardware, develop the software and ensure that both remain compatible.

Q. India has a huge Tier-2 and Tier-3 supplier ecosystem, but digital adoption remains uneven. How can technologies such as digital twins, simulation and AI reach smaller suppliers?

Most OEMs have access to advanced technologies, but adoption tends to decline further down the supplier ecosystem. Affordability and the ability to invest in advanced digital platforms are major factors.

Mahindra, for instance, has taken an approach of onboarding suppliers onto its digital environment. The idea is that vehicle design is an integrated activity, so suppliers need access to compatible technologies. However, smaller suppliers may not have the resources to make these investments themselves. An OEM can therefore acquire and host the software and provide suppliers with access.

For MSMEs further down the supply chain, we are also working with governments to establish Centres of Excellence, or what we call 'digital trial rooms'. These cloud-based centres allow MSMEs to access software under subsidised programmes for a limited period. They can design, simulate, validate and plan their products before taking the results to their shop floors.

We are working with state governments on such initiatives. One example is the Tamil Nadu Centre of Excellence for Advanced Manufacturing (TANCAM), developed with the Tamil Nadu Industrial Development Corporation. Similar initiatives have also been undertaken with the Karnataka government, with discussions ongoing with other states. The broader objective is to give suppliers across the value chain access to advanced digital technologies, from Tier-1 to Tier-N.

Q. EVs are changing the fundamentals of vehicle engineering, particularly batteries, thermal management, electronics and lightweighting. Which areas are seeing the fastest adoption of simulation and virtual engineering?

Simulation cuts across almost every aspect of EV development. It starts with vehicle architecture, where the body, chassis and structural elements have to be developed alongside the battery pack and thermal management system. Battery-pack validation and thermal management are particularly important. Simulation can involve both physics-based and chemistry-based approaches, allowing manufacturers to evaluate different battery technologies and chemistries.

For example, the requirements for a long-range EV can be evaluated virtually in terms of battery capacity, vehicle architecture and thermal management. Similar simulations can be performed for shorter-range vehicles. Simulation is particularly important for EVs because battery and energy-storage technologies are still evolving rapidly. Changes in battery chemistry can have implications for the entire vehicle. With AI expanding further, Machine-learning-based surrogate models can allow engineers to explore a much larger design space without running high-fidelity simulations for every alternative.

Instead of evaluating only a limited number of designs within a given timeframe, engineers can potentially explore thousands of alternatives. Once a promising design region is identified, high-fidelity simulations can then be used for detailed validation. This means the development process is moving from simply design, validate and produce towards design, simulate, optimise, physically validate and produce.

Q. Indian automakers are increasingly developing products specifically for export markets. Can India become a major global automotive product-development centre rather than primarily a manufacturing hub?

India's large domestic market itself represents a significant opportunity. The immediate focus can be on designing and manufacturing vehicles that are affordable and accessible to Indian consumers. This creates an opportunity to follow a 'design for India, make for India' approach while simultaneously building capabilities that can serve international markets.

Indian vehicles have evolved considerably in terms of technology and functionality, with domestic automakers developing increasingly sophisticated engineering, electronics and infotainment systems. However, international competitiveness is not determined solely by technology. Every market has its own regulatory frameworks, tariffs, duties and trade barriers. A vehicle may be technically competitive but become commercially challenging in a market because of these factors.

Geopolitical and geoeconomic considerations also influence export opportunities. India therefore has significant potential in both its domestic and international markets, with its growing technological capabilities providing a foundation for global expansion.

Q. Could we eventually see an entire vehicle manufacturing plant designed and tested virtually before construction begins, including production flow, robotics, worker movement and bottlenecks?

This is already happening through what we call the factory twin. Before a manufacturing plant is physically built or commissioned, its layout can be modelled digitally. This includes conveyors, racks, equipment, robots, automated guided vehicles and the movement of people. The factory can then be simulated to evaluate throughput and identify bottlenecks, slow-moving conveyors and other constraints.

Lastly, manufacturers can further optimise the layout to minimise conflicts between robots, machinery and workers, as it makes the manufacturing plants more flexible. A production line designed for ICE vehicles may eventually need to manufacture EVs, requiring significant reconfiguration.

Digital technologies allow manufacturers to make these changes virtually, validate the new configuration and then physically commission the plant. This is already being implemented in some manufacturing environments. The depth of adoption varies between organisations and markets, but the technology itself is already in use.

Q. Safety has become a major consideration for Indian car buyers, and ADAS has emerged as an important technology. What does the future of ADAS in India look like, and how can Dassault Systèmes contribute?

While ADAS is available in many vehicles, with applications ranging from automatic parking and collision detection to emergency braking, autonomous driving involves two dimensions: the technology and the environment in which it operates.

The technology can be modelled and developed, but accurately modelling the operating environment is more challenging. Indian roads present a particularly complex environment, with potholes, unpredictable traffic patterns, pedestrians, two-wheelers and animals.

ADAS systems therefore need to be trained and validated against a much wider range of scenarios than in more regulated traffic environments. Basic ADAS functionality is already available, while significant research is continuing globally and within the industry. From an Indian perspective, achieving higher levels of autonomous driving will require further development in simulation, validation and AI.

The challenge is not only the vehicle. The operating environment is equally important. Technologies that can accurately model and simulate Indian road conditions will therefore play an important role in improving the validation and safety of ADAS systems.

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