1. Introduction

Owing to global energy crises and stringent carbon emission regulations, the automotive industry faces unprecedented challenges. Aerodynamic drag constitutes over 60% of total resistance at speeds above 80 km/h, making it a key factor influencing vehicle energy efficiency [1]. Reducing the drag coefficient not only decreases fuel consumption in internal combustion engine vehicles but also extends the range of electric vehicles (EVs), positioning it as a focal point for academic research and industrial innovation. As the transition to electric vehicles accelerates, minimizing aerodynamic drag becomes not only an engineering challenge but also a strategic imperative for achieving net-zero emissions.

Recent advancements in aerodynamic optimization have shown remarkable progress. For instance, Tesla’s Model S achieves a Cd of 0.24 through streamlined contours and hidden door handles [2], while BYD’s Han EV reduces drag by 6% using an active rear spoiler [3]. Academic studies further highlight the potential of bio-inspired designs, such as shark-skin-inspired textures that reduce surface friction by 12% [4]. Technologies like synthetic jet actuators and plasma flow control also show promise in managing boundary layer separation [5]. Emerging innovations, including graphene-reinforced composites [6]and AI-driven shape morphing [7], are pushing the boundaries of lightweight and adaptive aerodynamic systems. Despite these achievements, challenges remain, including the high cost of lightweight materials and the reliability of adaptive systems.

This paper employs a literature review methodology to analyse existing aerodynamic optimization strategies, focusing on their technical principles, practical applications, and energy-saving effects. By synthesizing case studies and experimental data, the research aims to provide a comprehensive evaluation of current technologies and propose future innovation directions. New case analyses, such as Volkswagen’s ID.7 with integrated aerothermal management, and discussions on policy incentives, further enrich the exploration of multidisciplinary solutions. Linking theoretical insights with industrial practices, this study contributes actionable recommendations for developing next-generation low-drag vehicles aligned with global sustainability goals.

2. Literature review

2.1. Traditional body shape optimization: from streamlining to bio-inspired design

Traditional aerodynamic optimization primarily relies on streamlined body design and localized drag reduction. Hucho proposed that front-end streamlining significantly reduces pressure drag, while chassis smoothing minimizes turbulence generation [1]. For example, Tesla’s Model S employs a teardrop-shaped roof and hidden door handles to achieve a Cd of 0.24, representing a 20% improvement over conventional vehicles (Cd≈0.3-0.35) [2]. Mercedes’Vision EQXX further adopts a bio-inspired shark-like tail design, reducing rear vortex zones by 30% and achieving Cd=0.17 [8]. However, Lienhart and Becker cautioned that excessive streamlining may compromise cabin space and practicability, necessitating a balance between aesthetics and functionality [9].

2.2. Active aerodynamic systems: potential and limitations of dynamic control

Active aerodynamic systems dynamically adjust body components to optimize airflow. Joseph et al., in the Annual Review of Fluid Mechanics, reviewed synthetic jet and plasma actuator technologies, demonstrating their ability to delay flow separation and reduce drag by 10-15% [5]. Porsche’s Taycan features an adaptive rear wing that deploys at 200 km/h, increasing downforce by 50 kg while rising drag by only 2% [10]. Toyota’s patented machine learning-based algorithm (US20200198547A1) adjusts front lip and grille angles in real-time based on road conditions, reducing fuel consumption by 4% [11]. However, such systems face high costs and unproven durability [12].

2.3. Biomimetics and material innovations

Biomimetics offers novel solutions for aerodynamic challenges. Kim et al. showcased shark-skin-inspired microgroove structures, reducing surface friction by 12% [4]. Audi’s e-tron GT applies similar textures, lowering wind noise by 5% [13]. Beyond marine biology, avian-inspired designs are gaining traction. For example, MIT’s variable-stiffness skin, which mimics bird wing morphing, dynamically adjusting surface curvature, leading to an 8% reduction in trials [14]. In lightweight materials, carbon fiber composites (e.g., BMW 7 Series’ Carbon Core) reduce weight by 30% [15]. Recent studies also explore plant-based composites, such as Mercedes’ BIONEQXX^TM, which combines sustainability with a 40% weight reduction [16]. These innovations highlight how nature-inspired engineering can address both aerodynamic and environmental challenges. While traditional methods remain foundational, emerging technologies demand a paradigm shift toward adaptive and intelligent systems.

2.4. Emerging materials and intelligent control systems

Recent advancements in nanotechnology have introduced graphene-reinforced composites, which exhibit superior strength-to-weight ratios and self-healing properties. For instance, Volvo’s 2023 concept car integrates graphene panels, reducing weight by 25% while maintaining crash safety standards [6]. Additionally, deep learning algorithms are revolutionizing aerodynamic optimization. A study by Google DeepMind trained neural networks on 10,000 CFD simulations, achieving a 12% drag reduction in unseen vehicle models through real-time shape morphing [7]. These innovations highlight the convergence of material science and artificial intelligence in pushing aerodynamic boundaries.

3. Case studies

3.1. Tesla Cybertruck--breakthroughs and limitations of angular design

Tesla’s Cybertruck challenges traditional streamlining with its angular design (Cd=0.30). Laser-welded stainless steel panels reduce surface roughness by 8%, minimizing turbulence generation [17], while a seamless windshield-roof integration delays airflow separation, cutting rear vortex intensity by 15% [18]. Nevertheless, its angular profile compromises crosswind stability, with a 20% higher lateral force coefficient compared to the Model S [19]. Despite these trade-offs, the Cybertruck’s modular electronic architecture supports over-the-air (OTA) updates to dynamically adjust aerodynamic parameters, such as optimizing virtual side-mirror projections to reduce drag-inducing blind spots, showcasing the potential of software-defined vehicles. Future iterations may integrate retractable side skirts activated at highway speeds, balancing angular aesthetics with functional streamlining.

3.2. BYD Han EV--engineering practice of active aerodynamic attachments

BYD’s Han EV integrates an active rear diffuser and electric spoiler. STAR-CCM+ simulations optimized the diffuser angle to 25 degrees, increasing rear low-pressure zone pressure by 15% and reducing Cd by 0.03 [20]. Wind tunnel tests substantiated an 8% increase in range at a speed of 120 km/h [3]. The vehicle’s fully enclosed underbody panels minimize turbulence, reducing lift coefficient to -0.05 [21]. Real-world user data reveals a 12% reduction in energy consumption under urban-highway mixed driving conditions, validating the adaptability of active systems. This adaptability underscores the importance of context-aware aerodynamic control in diverse driving environments.

3.3. Mercedes Vision EQXX--bio-inspired design and energy efficiency limits

Mercedes’Vision EQXX features a shark-inspired body (Cd=0.17) and a solar roof. Its tapered rear design reduces vortex zones by 30%, while solar panels add 25 km of daily range [22]. BIONEQXX^TM, a plant-based composite, cuts weight by 40% and lifecycle carbon emissions by 60% compared to aluminum [16]. However, production costs remain triple those of conventional vehicles [23]. Recent trials demonstrated a record-breaking 1,200 km single-charge range, underscoring the synergy between bio-inspired design and lightweighting. Such advancements could democratize bio-inspired materials beyond luxury segments.

3.4. Volkswagen ID.7--integration of aerodynamics and thermal management

Volkswagen’s ID.7 exemplifies the synergy between aerodynamics and thermal efficiency. Its adaptive grille shutters close at high speeds to reduce drag (Cd = 0.23), while opening during cooling demands to channel airflow to batteries and motors, reducing battery temperature fluctuations by 15% [24]. Laser-etched surface textures, inspired by lotus leaf hydrophobicity, reduce water adhesion by 40%, minimizing drag in rainy conditions [25]. Field tests show a 7% range improvement in mixed weather scenarios, with only a 2 dB wind noise increase during heavy rain, outperforming competitors. Future plans include integrating phase-change materials (PCMs) into body panels to further optimize aerodynamic and thermal performance. These case studies collectively illustrate the trade-offs between radical design experimentation and practical engineering constraints, emphasizing the necessity for iterative prototyping and real-world validation.

4. Discussion

At present, current advancements in automotive aerodynamic optimization have transitioned from isolated shape design to a multidisciplinary system that integrates materials science, intelligent control, and cross-domain collaboration. Streamlined profiles, such as Tesla’s teardrop-shaped Model S (Cd = 0.24) [2] and Mercedes’shark-inspired Vision EQXX (8.3 kWh/100 km) [3], demonstrate significant improvements in energy efficiency by delaying airflow separation and reducing vortex generation. Bio-inspired surface treatments, including Audi’s shark-skin microgrooves (12% friction reduction) [10] and MIT’s morphing wing-inspired skins (8% Cd reduction) [12], further highlight the potential of nature-mimicking engineering. Active aerodynamic systems, such as BYD’s adaptive diffuser (Cd reduction of 0.03) [18] and Porsche’s deployable rear wing (50 kg downforce increase with minimal drag penalty) [6], exemplify how dynamic control can balance performance and efficiency. Lightweight materials, ranging from carbon fiber composites (30% weight reduction) [11] to cost-effective magnesium alloys (40% lighter than carbon fiber) [15], underscore the importance of material innovation in reducing energy consumption.

However, challenges persist in translating these technologies into mass-market solutions. High costs remain a critical barrier, with carbon fiber bodies priced 300% above steel [26] and active aerodynamic systems exceeding $500 per unit [5]. Multidimensional trade-offs, such as the conflict between fully enclosed underbodies and thermal management requirementsl [27], complicate design processes. Standardization gaps, including the lack of protocols for testing active components [28] and policy incentives for aerodynamic efficiency [26], further hinder progress.

Future research needs to prioritize cost-effective technologies, such as recycled carbon fiber (40% cost reduction) [29] and magnesium die-casting [30], while advancing intelligent multidisciplinary design frameworks. AI-driven optimization tools, like Rimac’s real-time wing adjustments [20], and digital twin platforms (2% model error) [31], offer pathways to harmonize aerodynamics with thermal and structural demands. Policy initiatives, such as aerodynamic efficiency labeling [32] and industry collaborations for material R&D [33], are equally critical to accelerate adoption. For instance, California’s 2025 Zero-Emission Vehicle (ZEV) regulations now include aerodynamic efficiency thresholds (Cd < 0.26), incentivizing automakers to adopt active grille shutters and enclosed underbodies [32]. Regulatory frameworks need to evolve to incentivize aerodynamic efficiency, mirroring the success of emissions standards in driving technological adoption. Concurrently, public awareness campaigns can bridge the gap between technical advancements and market acceptance, fostering demand for low-drag vehicles.

5. Conclusion

This study systematically evaluates the technical, economic, and regulatory dimensions of automotive aerodynamic optimization. Key findings reveal that streamlining, active systems, and lightweight materials collectively improve energy efficiency by 30–50%, with innovations like graphene composites and AI-driven shape morphing pushing the boundaries of drag reduction. Cross-domain approaches, such as bio-inspired textures and adaptive control algorithms, are pivotal for future breakthroughs. However, commercialization faces significant hurdles, including high costs, design trade-offs, and standardization gaps. To address these challenges, large-scale road testing, multiphysics simulations, and scalable material solutions must be prioritized.

While this study provides a comprehensive theoretical framework for aerodynamic optimization, it primarily relies on literature reviews and case analyses, with limited validation through original experimental data or computational simulations. For instance, the impact of real-world conditions (e.g., crosswinds, road roughness) on aerodynamic performance remains underexplored. Future work will integrate field testing across diverse climates and terrains to quantify practical energy savings. Additionally, advanced multiphysics simulations coupling aerodynamics, thermal dynamics, and structural mechanics will be developed to refine predictive models. Collaborative efforts with automotive manufacturers will further validate the scalability of bio-inspired materials and AI-driven control systems.

In summary, aerodynamic optimization is central to achieving carbon-neutral transportation. Through technological innovation, policy support, and consumer education, the vision of commercializing“zero-drag”vehicles can propel global sustainability efforts. The integration of science, industry, and societal needs will ultimately define the success of next-generation automotive engineering.