WORKING DRAFT

Last Modified 12.06.2018 14:50 W. Europe Standard Time

Printed 12.06.2018 14:52 W. Europe Standard Time

McKinsey and Global Semiconductor Alliance | Munich, June 4 2018

Automotive Electronics Architecture

of the Future – Implications for semiconductor

companies

WORKSHOP DOCUMENT

CONFIDENTIAL AND PROPRIETARYAny use of this material without specific permission of McKinsey & Company is strictly prohibited

Last M

odifie

d 1

2.0

6.2

018 1

4:5

0 W

. Euro

pe S

tandard

Tim

eP

rinte

d 1

2.0

6.2

018 1

4:5

2 W

. Euro

pe S

tandard

Tim

e

2McKinsey & Company

Background and purpose of our workshops

Background: GSA-McKinsey cooperation

▪ Intensive research collaboration focusing on the

most relevant topics for the semiconductor industry

– The Internet of Things – opportunities and

challenges for semiconductor companies (2015)

– Security in the Internet of Things (2016)

▪ Project steering by GSA EMEA Executive Forum,

with knowledge input through interviews and

surveys by many industry players / GSA members

▪ Publications and wide industry dissemination

Current hot topic: automotive electronic and software trends – what does it mean for semiconductor companies?

▪ Recent developments and trends in automotive electronics

are on top of mind for many industry leaders and GSA

members

▪ Key challenges is that this is a deeply technical topic that

has significant strategic implications for many players

across the value chain

▪ In 2 workshops in November 2017, we discussed and

aligned on 10 hypotheses on the future technology

evolution of automotive electronics & software

▪ Goal of this workshop is to recap those trends and then

discuss the implications and learnings for incumbent

semiconductor companies

Last M

odifie

d 1

2.0

6.2

018 1

4:5

0 W

. Euro

pe S

tandard

Tim

eP

rinte

d 1

2.0

6.2

018 1

4:5

2 W

. Euro

pe S

tandard

Tim

e

3McKinsey & Company

Software is the core enabler for key automotive innovations in connectivity, autonomous driving,

electrification and diverse mobility and thus increasingly becomes a differentiating factor

SOURCE: McKinsey & Company Analysis, IEEE "This Car Runs on Code"; HAWK; Automotive Electronics Initiative

Connectivity

▪ Integration of 3rd party services

▪Updates over-the-air to deploy

new features faster

▪Operation of future cars partly in

the cloud

Autonomous driving

▪Rise of built-in sensors and

actuators

▪Higher demand for computing

power and communication

▪Unlimited need for reliability

Diverse mobility

▪Shared mobility services and

robo-taxis via app

▪Customized driver experience

Electrification

▪ Introduction of new electronics

▪Reduction of energy

consumption through advanced

software algorithms

Innovation through software

Last M

odifie

d 1

2.0

6.2

018 1

4:5

0 W

. Euro

pe S

tandard

Tim

eP

rinte

d 1

2.0

6.2

018 1

4:5

2 W

. Euro

pe S

tandard

Tim

e

4McKinsey & Company

Increasing complexity in software is a key challenge for the automotive industry – modern

vehicle architecture has to be adjusted in order to manage complexity and quality

SOURCE: McKinsey & Company Analysis, IEEE "This Car Runs on Code"; HAWK; Automotive Electronics Initiative

Software lines of code (SLOC), millions

A modern car is a computer on wheels,

differentiated by the software features it offers

Already in the last years, software applications in vehicles have seen a dramatic increase in size and complexity…

…leading to significant quality issues caused by faulty software implementations

EXEMPLARY

▪ Recall of 1.9M hybrid cars

▪ Recall of 143,000 cars in the US

▪ Recall of 65,000 cars

▪ Recall of ~1.4M cars

▪ SW security flaw made cars vulnerable to hackers

▪ SW flaw may cause the hybrid system to shut down while driving

▪ Flaw in the continuously vari-able automatic transmission software may subject the drive pulley shaft to high stress

▪ SW flaw may cause vehicle doors to be unlatched

▪ Flaw in engine control unit SW may cause engine to stop while stopping at a traffic light

▪ Recall of ~3,000 cars

To ensure safety in increasing degrees of autonomy, software quality and complexity are a key challenge for the automotive industry, requiring a rethink today’s vehicle software and E/E architecture

~ 10

~150

20162015

~ 100

2010

x 1,5

x 10

Last M

odifie

d 1

2.0

6.2

018 1

4:5

0 W

. Euro

pe S

tandard

Tim

eP

rinte

d 1

2.0

6.2

018 1

4:5

2 W

. Euro

pe S

tandard

Tim

e

5McKinsey & Company

Not surprisingly, many players active in the automotive electronics arena today are expanding

their focus area along the stack

EXAMPLES

SOURCE: McKinsey & Company

Emerging activitiesExisting playersNew players

Hardware abstraction

Firmware

Applica-tions

Operating system

Signal processing

Tier-2/-3 OEMTier-1

Premium car OEM

Volume/low-cost car OEM

Auto soft-ware/SW environment supplier

Car electronics system supplier

Semi-conductor supplier

Integrationarchitects

FeaturesSW giants / Tech players

Hardware

Does not reflect non-embedded applications / software (e.g., cloud-based) that interacts with vehicle

Computing and connectivity players

Last M

odifie

d 1

2.0

6.2

018 1

4:5

0 W

. Euro

pe S

tandard

Tim

eP

rinte

d 1

2.0

6.2

018 1

4:5

2 W

. Euro

pe S

tandard

Tim

e

6McKinsey & Company

The vehicle architecture will become more layered – new layers for connectivity, applications, artificial

intelligence and operating system will be added

SOURCE: McKinsey & Company

1 Strong rise in number of applications - application layer exists already today 2 Incl. OS in status quo

Today's differentiation through:

▪ Vehicle hardware

▪ UI/UX

Software is partially vertically integrated in the current architecture, i.e., some software in ECUs

...will shift to future factors for brand differentiation in:

▪ Infotainment features requiring Plug & Play capabilities

▪ Autonomous capabili-ties including sensor fusion algorithms as complement to hardware

▪ Safety features based on fail-operational behavior

▪ Software will move further down to hardware (smart sensors)

▪ Stacks become horizontally integrated

▪ New layers will be added to the stack

Vehicle

Middleware layer/OS

E/E hardware2

UI/UX/HMI

Connectivity (back-haul)

Artificial intelligence / Advanced analytics

Sensors ActuatorsPower

components

Cloud platform

Applications1

FROM: Partially vertically

integrated architecture TO: Layered in-vehicle and backend architecture

Combine in-vehicle data with environmental data

Significant increase in number of applications, moving into a service-oriented architecture with interdependent services

Abstract applications from hardware

Analyze data for real-time decisions and autonomous driving

Modified layersNew layers

< >

Closely controlled add-on apps and modulesdue to safety reasons

Last M

odifie

d 1

2.0

6.2

018 1

4:5

0 W

. Euro

pe S

tandard

Tim

eP

rinte

d 1

2.0

6.2

018 1

4:5

2 W

. Euro

pe S

tandard

Tim

e

7McKinsey & Company

The E/E architecture has evolved from independent function – specific ECUs towards a

centralized architecture

Generation High-level architecture

Vehicle centralized E/E architecture

Domain centralizedE/E architecture

Distributed E/E architecture

Main features

2nd generation

▪ Collaboration of ECUs within one domain

▪ Domains: body/comfort, chassis, powertrain,and infotainment

▪ 3-4 independent networks

▪ Limited communication between domainsInfotainment

Body/comfort Chassis

Power-train

4th generation

▪ Central domain controller

▪ Ability to handle more complex functions, e.g. L3 HAD

▪ Consolidation of functions (cost optimization)

Domain controller

1st generation

▪ Independent ECUs

▪ Isolated functions

▪ Each function has its ECU (1:1 connection)

Today

3rd generation

▪ Stronger collaboration via central gateway

▪ Cross-functional connection

▪ Ability to handle complex functions, e.g. ACC

Central GW

5th generation

▪ Virtual domain

▪ Limited dedicated hardware

▪ Ethernet backbone

▪ High complex, high compute functions

▪ Suitable for L4-L5 HADSensor Actuator

Gateway

Infotain-ment

Focus of the document

Outlook

Last M

odifie

d 1

2.0

6.2

018 1

4:5

0 W

. Euro

pe S

tandard

Tim

eP

rinte

d 1

2.0

6.2

018 1

4:5

2 W

. Euro

pe S

tandard

Tim

e

8McKinsey & Company

10 working hypotheses for the automotive software and E/E architecture of the future

2

Expanded middleware layer will abstract applications from the hardware: On top of ECU hardware in the car, the middleware layer will allow for abstraction and virtualization, a service-based architecture, and distributed computing

4

Full redundancy of power and data networks: (Safety-) critical applications will require fully redundant circles for data transmission and power supply that are intelligently controlled to support steer-by-wire and other HAD functions

3

Limited number of architecture stacks with integrated hardware and software: The number of stacks will decline, but stacks per se will remain and will be connected with each other. Stacks will be optimized within themselves

5 Sensors will become more intelligent: Intelligence will likely move from ECUs into sensors. Future sensors can pre-process data for simple calculations, trigger actuators directly, and inform ECUs retrospectively about the actions – HAD will require central computing to connect sensors

1 ECUs are getting consolidated: Instead of a multitude of specific ECUs for specific functionalities, the industry will move to a consolidated vehicle architecture driven by costs, new market entrants, and demand from HAD – on the long-term, further virtualization will lead to more SW agnostic HW

6

Significant mid-term spike in the number of in-vehicle sensors: Sensors with similar functionalities will be installed in the next 2-3 vehicle generations to ensure functional safety – in the long-term, OEMs will opt for specific sensor solutions to reduce the number of sensors/costs

8

Increasing use of cloud to combine in-vehicle data with environmental data: Data that is neither safety-critical nor personal will be increasingly processed in the cloud to derive additional insights

9

Rise of automotive Ethernet: Due to increased data rates and redundancy requirements for HAD, automotive Ethernet will emerge as a key enabler, especially for the central data bus

7

Data connectivity for functional safety and ADAS will always be channeled via the OEM; more open interfaces in infotainment: Central connectivity gateways transmitting/receiving safety critical data will always connect solely to an OEM backend which 3rd parties can connect to for data access. In infotainment, more open interfaces will allow for deployment of content according to standards set by the OEM

10 Components will be updateable and communicate bi-directionally: Test systems in the vehicle allow for function and integration tests of updates, which form the basis of lifecycle management and post-purchase feature enhancement/unlocking. All ECUs will be able to send and receive data to/from sensors/actuators. Data sets can be retrieved to support innovative use cases (e.g., route calculation based on vehicle parameters).

SOURCE: McKinsey

Last M

odifie

d 1

2.0

6.2

018 1

4:5

0 W

. Euro

pe S

tandard

Tim

eP

rinte

d 1

2.0

6.2

018 1

4:5

2 W

. Euro

pe S

tandard

Tim

e

9McKinsey & Company

Potential disruptive developments – „what ifs“ and their implication for semiconductor companies

What if…

…OEMs significantly invest into capabilities around the right electronics hardware to specify chips in a way that they move to become their “own fabless” semicon supplier?

…Tier-1 suppliers make a decisive push to provide integrated ADAS/HAD systems fully commoditizing the underlying hardware?

…intelligence in a vehicle is truly centralized resulting in demand on semiconductors primarily for a central supercomputer while decentralized chipsets are almost fully substituted/reduced to very basic functionality?

…industry standardization of the hardware stack incl. virtualization leads to a commoditization of chips similar to PCs?

For discussion:

▪ How realistic would you see those

disruptive scenarios?

▪ How could semiconductor companies

setup themselfs to prepare for such

developments?