Economic impact of ACES trends on the automotive value chain: a forecast exploratory study of the Chinese automotive industry in 2030

Green transportation aims to reduce traffic congestion and environmental pollution and is characterized by a revolution in autonomous, connected, electric, and shared (ACES) vehicles. The next decade is expected to be a key period for the widespread adoption and implementation of ACES trends. The paper argues that exploring the economic impact of ACES trends on the automotive industry in 2030, from a value chain perspective, has significant implications. China plays a pivotal role, serving as a hub for R&D, production, and sales of intelligent and connected vehicles. New vehicle sales have exceeded 20 million annually, and the Chinese vehicle stock reached 336 million in 2023, projected to rise to 434 million by 2030 (a growth of 29.17%). The growth rate of vehicle stock is decreasing, indicating a transition from an incremental to a stock-driven market and signaling a new growth point for the automotive industry. The sharing trend primarily affects usage patterns and consumption attitudes but has negligible impact on the vehicle’s structure and thus on the value chain; therefore, this paper focuses on automation, interconnection, and electrification. According to SAE J3016, L0–L2 correspond to ADAS; L3–L4 can autonomously drive in specific scenarios; L5 is fully autonomous. In this paper, AVs are defined as vehicles equipped with L3 and above; vehicles at L2 and below are NAVs. McKinsey’s optimistic expectation is that 15% of new vehicles will reach L4 in 2030, with AVs accounting for 66% of new vehicle sales; the pessimistic expectation posits AV mass production only after 2027 and AVs less than 10% of 2030 new sales. Electrification brings environmental benefits and significant structural changes. In Chinese practice, vehicles are categorized as NEV (BEV and PHEV), HEV, and ICEV. Batteries and electric powertrains replace fuel tanks, engines, and gearboxes. In intelligence, high-performance AI chips replace many distributed ECUs via centralized architectures, and new sensors and in-vehicle software enable environment perception and automated driving. Against this backdrop, the paper targets two questions for 2030: (1) What is the installation scale and market size of China’s automotive production value chain? (2) What is the income change of China’s automotive aftermarket value chain?

The literature on ACES is grouped into technologies and impacts. On technologies, advances in communications, security, intersection navigation, collision avoidance, and pedestrian detection underpin connected and automated vehicles (CAVs). Reviews highlight substantial progress in ADAS and vehicle-to-vehicle (V2V) capabilities, with limited integration of vehicle-to-infrastructure (V2I), signaling a need for future research integrating V2I to fully realize CAV benefits. On impacts, extensive studies assess environmental outcomes, road safety, capacity and efficiency, public attitudes, and socio-economic effects. Environmental effects of CAVs are mixed and context-dependent across vehicle, transport system, urban, and societal levels. Economically, scenario-based analyses suggest profitable opportunities for sectors such as automotive, electronics/software, telecommunications, data services, digital media, and freight, while insurance and maintenance/repair may face revenue pressures. Prior work on China qualitatively examined value chain impacts of intelligent connected vehicles. However, quantitative research on ACES economic impacts remains scarce due to the brief history of ACES vehicles and limited market data. Building on Porter’s value chain theory, this study quantitatively analyzes the economic impact of ACES on the automotive value chain, focusing on production (power batteries, electric powertrains, sensors, in-vehicle software and chips) and the aftermarket (maintenance, wearing parts replacement, repair, tires, accident repair). It poses two research questions for China in 2030: (1) installation scale and market size of production; (2) income changes in the aftermarket.

The paper proposes an analytical framework linking AV stock in 2030 to quantitative estimates for production installation scale/market size (power batteries, electric powertrains, sensors, in-vehicle software and chips) and aftermarket income (maintenance, replacement of wearing parts, repair, tire, accident repair). AV stock estimation: Assuming AVs popularized after 2023 will not be scrapped before 2030 (typical service life >12 years), AV stock in 2030 is computed by aggregating annual new vehicle sales multiplied by the AV ratio, accounting for stock changes and scrappage at a 4% rate. The composition of 2030 new sales and stock under optimistic and pessimistic AV penetration scenarios is calculated accordingly. Production segment: For each component o (e.g., battery, powertrain, sensors, software, chips), the installation scale is the sum over vehicle types of average installed quantity per vehicle times sales volume; market size is installation scale times average cost. Vehicle types include combinations of intelligence levels (NAV vs AV) and electrification (BEV, PHEV, HEV, ICEV). Assumptions for BEV and PHEV battery capacities/costs use the China SAE technology roadmap and CLTC ranges (e.g., 84 kWh BEV pack, 8.4 kWh PHEV pack) to derive installed capacity and market size. Aftermarket segment: The aftermarket is narrowly defined into five income categories: maintenance (filters, wiper blades, spark plugs, engine oil, others), replacement of wearing parts (battery, brake, chassis/suspension, others), repair (engine, gearbox, drive shaft, wheel, electronics, others), tires, and accident repair. Material income (parts) is modeled; labor income is excluded due to confounding factors. For each category, total income equals vehicle stock times average income per vehicle, allocated across sub-items by proportions. Relative growth considers effects of intelligence (M_i) and electrification (N_j) on sub-items. Intelligence effects include smoother AV driving reducing certain wear and accidents; electrification effects include regenerative braking reducing brake wear, removal of ICE components, and increased electronics content. Tires are assumed to scale with total vehicle stock (mileage dependence only). Accident repair is modeled holistically as the product of encounter probability of two vehicles, their collision probability upon encounter, and average repair income per accident, with adjustments for AV vs NAV encounters and a 10% higher repair income for AVs (reflecting 10% higher new vehicle price). AV–AV collision probability is reduced to 1% of NAV–NAV; AV–NAV collision probability is 50% of NAV–NAV. The framework computes per-vehicle and total income changes under optimistic and pessimistic AV penetration scenarios for 2030.

Vehicle stock and AV penetration (2030): - Under optimistic expectations, AVs comprise 66.09% of new sales (1,898.45/(1,898.45+973.94)×100%) and 17.63% of stock (7,650.76/(7,650.76+35,749.24)×100%). Under pessimistic expectations, AVs remain rare (new sales 56.38 vs 2,816.01 for NAV; stock 110.48 vs 43,289.52, each in 10,000 units). Production value chain in 2030: - Power batteries: Total installed capacity ~1.04 TWh; total market size ~USD 81.532 billion (BEV ~USD 80.606 bn; PHEV ~USD 0.926 bn). Compared to 2023 (0.387 TWh; USD 55.02 bn), 2030 capacity is 2.69× and market size is 1.48×. - Electric powertrains: Overall market projected to be ~1.88× 2023; BEV powertrain market ~2.42× 2023. - Sensors: Total 2030 market size estimated at USD 63.27 bn (optimistic) vs USD 13.00 bn (pessimistic); AV sensor market USD 59.38 bn (opt) vs USD 1.76 bn (pess). - In-vehicle software: Total USD 35.57 bn (opt) vs USD 8.75 bn (pess); AV portion USD 32.88 bn (opt) vs USD 0.98 bn (pess). - Chips: Total USD 67.77 bn (opt) vs USD 24.92 bn (pess); AV portion USD 59.76 bn (opt) vs USD 1.77 bn (pess). Aftermarket value chain in 2030: - Tires: Total income grows in line with stock (+29.17% vs 2023); per-vehicle income unchanged. - Maintenance: Average income per vehicle −13.92%; total income +11.18% (below stock growth). Sub-item dynamics (per-vehicle): BEV reduces filters (−75%), spark plugs (−100%), engine oil (−100%); increases others (+70% for EV-specific items). (P)HEV increases others (+35%); AV effects negligible. - Replacement of wearing parts: Average per-vehicle −11.26% (opt) / −9.15% (pess); total +14.62% (opt) / +17.35% (pess). AV smoother driving reduces brake/suspension wear (−20%). Electrification/regeneration reduces brake wear (−33%) and 12V battery replacements (−30%); BEV reduces others (−10%). - Repair: Average per-vehicle −4.1% (opt) / −5.5% (pess); total +23.87% (opt) / +22.06% (pess). AV smoother driving reduces engine/gearbox/drive shaft repairs (−15%); BEV eliminates gearbox repairs (−100%), reduces engine-related repairs (−80%), increases electronics (+50%); (P)HEV electronics +25%. Electronics share grows markedly (e.g., total repair income electronics change +69.05% opt). - Accident repair: Per-vehicle average −16.87% (opt) / −0.24% (pess); total +7.38% (opt) / +28.85% (pess), reflecting reduced collision probabilities with AV adoption and increased total stock. AV–AV collisions drop to 1% of NAV–NAV collision probability; AV–NAV to 50%; AV repairs are 10% costlier per accident. Overall: ACES create substantial new production markets (batteries, powertrains, sensors, software, chips). Electrification and intelligence reduce average aftermarket income per vehicle, but total aftermarket income still rises on the back of a larger vehicle stock by 2030.

The study’s findings address the research questions by quantifying both production-side market creation and aftermarket income shifts under ACES trends for China in 2030. Production is structurally reshaped: batteries and electric powertrains replace ICE components, and AVs drive demand for sensors, high-performance computing platforms, chips, and complex software. These emerging segments yield sizable market opportunities by 2030 across optimistic and pessimistic AV uptake scenarios. On the aftermarket, electrification reduces routine maintenance items tied to ICE (oil, spark plugs, several filters) and, with regenerative braking, reduces wear on brakes; intelligence promotes smoother driving and fewer accidents. Consequently, average per-vehicle material income declines across maintenance, wearing parts replacement, and repairs. However, due to continued growth in vehicle stock (projected +29.17% by 2030), total aftermarket material income still grows, though often below the stock growth rate, with tires tracking stock and electronics-related repairs increasing. Accident repair totals vary with AV penetration: lower per-vehicle accident income is counterbalanced by stock growth; higher AV shares produce lower total growth in accident repair than pessimistic scenarios. These quantitative insights clarify where value migrates along the automotive value chain: away from ICE-centric components and per-vehicle aftermarket spend, toward electrified propulsion and intelligent systems. For industry stakeholders and policymakers, the results signal the need to reallocate investments toward battery value chains, power electronics, sensing, software, and semiconductor capabilities, and to adapt aftermarket strategies to EV- and AV-specific service needs (e.g., electronics and thermal systems).

This exploratory quantitative study examines how ACES trends will restructure China’s automotive value chain by 2030. On the production side, the installed capacity and market size of power batteries, electric powertrains, sensors, in-vehicle software, and chips expand substantially (e.g., battery capacity 2.69× and market size 1.48× vs 2023; electric powertrains ~1.88×; significant AV-driven markets for sensors, software, and chips). On the aftermarket side, electrification and intelligence reduce average per-vehicle material income across maintenance, wearing parts, repairs, and accident repair, while total income generally rises due to increased vehicle stock (tires tracking stock growth; electronics repair rising). The paper contributes a business-oriented, value-chain perspective with quantitative estimates useful for strategy and policy. Future research should strengthen data breadth and model sophistication and extend analyses beyond China to assess cross-country similarities and differences, enabling a more comprehensive global understanding of ACES impacts and best practices.

The study is exploratory and constrained by limited available market data for ACES and simplified mathematical representations. Estimates rely on assumptions (e.g., scrappage rates, AV penetration scenarios, component cost/usage profiles) that may evolve. Analyses focus on China; generalizability to other countries is uncertain due to differing market structures, policies, and adoption trajectories. Future work should compile more comprehensive datasets, apply more sophisticated modeling, and conduct comparative multi-country analyses to enhance robustness and external validity.