Tracking The Tipping Points for Automotive Industry

Photo by Vlad Tchompalov on Unsplash

“The tipping point is that magic moment when an idea, trend or social behavior crosses a threshold, then tips and spreads like a wildfire.” — Malcom Gladwell

Automotive industry is known to be cyclical in nature: it thrives during a period of economic prosperity and suffers from lower sales during economic upheavals (downturns and recessions). It correlates strongly with GDP figures. When such an industry faces multiple tipping points in a quick succession (or in an overlapping manner), the industry dynamics are bound to invert.

• Incumbents face a juggling task to maintain status quo, all the while making huge investments towards new trends in products and technology. What makes this challenge more perilous for incumbents is the need for rapid technological innovation and shortened product development cycles that are core competencies intrinsic to startups.
• Tipping points also encourage new entrants (who might predict these magic moments earlier than the incumbents) to work on technological bets that will catapult them to glory in a historically capital-intensive, oligopolistic auto-industry.

Let’s take a look at few of the tipping points. Let’s start with those that haven’t been covered extensively.

Tipping Point 1: Optimized Electronic/Electrical (E/E) System Architecture

Why should we call this a tipping point? The Electronic/Electrical architecture within vehicles has reached a critical stage in its lifecycle. Its complexity has increased over the years due to historically convenient practices: “every time a new feature is to be introduced, add a new ECU box” has been the norm for decades.

But, automakers are now taking cognizance of the hardware-induced architectural complexity. They have become aware that in order to avoid scalability issues when we take into account the advent of autonomous driving capabilities, this complexity needs to be dealt with. Many OEMs have now introduced optimally designed E/E architectures in their new vehicle platforms.

These new architectures are characterized by:

1. Consolidation in the number of ECUs and a modular design
2. Division of E/E System into zones (zonal controllers)
3. Separation of core computing from I/O (to simplify assembly and cloud integration)

Such an architecture will form a standard backbone for software features introduced as part of autonomous driving.

Tipping Point 2: Digital Automotive Design (DAD)

(DAD: Decoupling of vehicle hardware and software by introducing an abstraction/middle-layer platform in the technology stack )

Let’s look at an analogy. Operating systems like iOS and Android have decoupled the underlying hardware components from mobile applications that function on top. Developers use these platforms to deploy their apps through App Stores without taking into consideration the nitty-gritties of the hardware components involved under the hood. These middle-layer operating systems/platforms ensure an abstraction layer that speeds up feature development, deployment and ongoing software updates for years.

Similar design philosophy is being considered for automotive design by companies like NIO in China.

DAD is characterized by:

1. Standardized commodity hardware components that handle multiple functions
2. A middle layer that abstracts the underlying hardware (much like virtualization in computer system parlance) and supports scalability
3. Feature differentiation handled at software level rather than at hardware level within the vehicle stack
4. DAD as a backbone for continued Over-The-Air (OTA) software updates to modify/add features to a vehicle

Tipping Point 3: OTA Updates and Subscription Business Model

Automakers around the globe are following Tesla’s footsteps (which functions less like an automotive manufacturer and more like a software company) to enable OTA (over-the-air) software updates within their vehicles. As is the case with OTA updates in mobile phones, these updates are used to add new features and crease out functional & security bugs on an ongoing basis.

This is in stark contrast to the traditional business model in automotive industry. Once a customer bought a vehicle at a dealership with specifications of his choice, updates to core functionalities were not feasible. Any future recalls and repairs were done at the dealers.

However, with the advent of OTA software updates (clubbed with a software-driven digital automotive design), a vehicle’s functionality could be updated/upgraded years after its date of purchase. The OEM could even bring in a subscription-based business model into the equation where the customer can pay a monthly fee to get specific feature-sets enabled in his vehicle post-purchase from a dealership.

Note: OTA updates have raised concerns around existing ‘Right to Repair’ laws. When a major part of vehicle maintenance is handled through software updates tightly controlled by OEMs, vehicle owners and mom-&-pop repair shops would fail to conduct any DIY repairs to future vehicles, unless the vehicle manufacturers share architectural and telematics data with them.

Tipping Point 4: Autonomous Vehicles (AVs)

AV system stack is characterized by:

1. Sensors: Physical Hardware (Radars, Lidars, Cameras, IMU)
2. Perception: Using sensors to visualize the environment. It involves two steps — Detection & Localization. Detection uses sensor data to detect objects. Localization determines the position of the vehicle in respect to the external environment using HD Mapping.
3. Planning: Planning system uses data points gathered in the perception system to create path-points for the vehicle to follow. This stage also predicts the movements of other vehicles around and updates the path-points accordingly.
4. Control: The Control system takes in data from the Planning system and actuates vehicle movements — acceleration, braking, steering etc.

With the advances in AI, cloud computing and edge computing, possibilities of creating an ecosystem-on-wheels that can support varied smart/shared mobility use cases have increased. Imagine a digital business ecosystem governed through vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P) and vehicle-to-network (V2N) communications.

Let’s try to predict and list down an evolution path for AV use cases:

• Consolidation among industry players
• Robo-taxis as a part of shared-mobility ecosystem
• Autonomous commercial vehicles and cargo trucks for highway transportation
• Urban driving by consumers (by 2030)

Note: Above tipping point refers to SAE Level 4/5 autonomous vehicles.

Tipping Point 5: Electric Vehicles (EVs) & vertically-integrated supply chain

Tesla’s consecutive profitable quarters, their market capitalization and their close to half a million vehicle deliveries in 2020 — if that’s something to go by, EVs are the undisputed future of automotive industry, replacing the ICE (internal combustion engine) counterparts and on the way to account for a third of vehicles sales by 2025.

Factors that contributed to Tesla’s success and resulted in huge investments for electrification from other incumbent OEMs include — stricter regulations on emissions, government incentives like tax credits (& hence a lower ownership cost) and advances in battery technology.

If we look at Tesla’s playbook (their Blue Ocean Strategy) to establish themselves:

• Step 1: Develop a luxury sports car with a price premium for a niche market (a lifestyle product)
• Step 2: Use the traction and money to create a mass-market affordable vehicle

Their way to glory has also seen what Elon Musk called a ‘production hell’ when delivery timelines for vehicles were not met, over-automation on plant floor resulted in unit losses and quality suffered. This has showed that it is difficult for any new entrant in the industry to be at par with incumbent OEMs when it comes to manufacturing vehicles at scale — a competency developed over decades of production experience. But, EV market is not an easy ride for incumbent OEMs as well. Tesla’s software focused design and development strategy is difficult to replicate if not impossible.

Tesla has organized itself within a tight vertically-integrated business model. R&D and manufacturing of core EV components (battery packs and computing hardware) is done in-house and this is predicted to be a sustainable competitive advantage for years to come. Vertical integration could also create entry barriers, scale economies and cost savings.

Tipping Point 6: Battery Technology and Charging Infrastructure

(This tipping point is correlated to point 5)

Today, two major factors that govern an EV purchase decision for a customer are: range (miles) and availability of charging infrastructure. Tesla has managed to stay ahead on both of these factors with their long range variants offering industry-leading range-figures and their superchargers having a significant presence in the markets where Tesla vehicles are sold.

However, there is a huge scope for improvement in current lithium-ion batteries used by most of the OEMs. Energy density could be improved to provide more range. Charging time could be reduced further (from more than an hour for a full charge right now). Solution?

A startup — QuantumScape, enters the arena. The startup, mid last year, announced their ‘solid-state battery’ that overcomes the downsides of existing lithium-ion batteries with faster charging time and a higher energy density.

Few other OEMs have also ventured into developing their solid-state batteries targeting them to be on road by 2025.

Rahul Nilangekar is a Product Manager, Entrepreneur and a budding Writer. He received his MBA from the Indian Institute of Management, Lucknow in India. His corporate work experience spans across the IT services industry and the Automotive industry.