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This paper is part of a broader research project aiming at studying, designing, and prototyping a hydrogen-powered internal combustion engine to achieve fast market implementation, reduced greenhouse gas emissions, and sustainable costs. The ability to provide a fast market implementation is linked to the fact that the technological solution would exploit the existing production chain of internal combustion engines. Regarding the technological point of view, the hydrogen engine will be a monofuel engine re-designed based on a diesel-powered engine. The redesign involves specific modifications to critical subsystems, including combustion systems, injection, ignition, exhaust gas recirculation, and exhaust gas aftertreatment. Notably, adaptations include the customization of the cylinder head for controlled ignition, optimization of camshaft profiles, and evaluation of the intake system.

The 2023 FISITA White Paper (for which the author was a contributor) on managing in-service emissions and transportation options, to reduce CO2 (CO2-e or carbon footprint) from the existing vehicle fleet, proposed 6 levers which could be activated to complement the rapid transition to vehicles using only renewable energy sources. Another management opportunity reported here is optimizing the vehicle’s life in-service to minimize the life-cycle CO2 impact of a range of present and upcoming vehicles. This study of the US vehicle fleet has quite different travel and composition characteristics to European (EU27) vehicles. In addition, the embodied CO2 is based on ANL’s GREET data rather than EU27 SimaPro methodology. It is demonstrated that in-service, whole-of-life mileage has a significant influence on the optimum life cycle CO2 for BEVs and H2 fuelled FCEVs, as well as ICEs and PHEVs.

​Composites made of continuous fibers generally have higher strength-to-weight ratios in fiber directions as compared to those made of discontinuous fibers. However, the latter tend to display quasi-isotropic properties which can be of advantage when directions of mechanical loading can vary. For many real-world applications such as robust design of vehicle body components for crashworthiness, impact loads are stochastic in nature both in terms of magnitude and direction. Hence, in order to realize the true potential of laminated composites with continuous fibers, instead of orthotropic laminates which are most common due to the ease of design and manufacturing, angle-ply laminates are necessary.

The ball joint with cross groove offers both angular and plunging motion. When transmitting the same torque, the cross groove ball joint is lighter than other plunging Constant Velocity Joints (CVJs). It is crucial for the design of the joint and enhancing the contact fatigue life of the raceway to accurately estimate component loads of the ball joints with cross groove. In this study, the transmission efficiency of the joint and the peak value of contact force between ball and the track are used as evaluation indexes for characterizing dynamic performance of the joint. A multibody dynamic model of the joint is established to calculate its dynamic performance. In the model, the contact properties and friction characteristics of the internal structures were modeled, and a nonlinear equivalent spring and damping model was adopted for estimating the contact force. The transmission efficiency loss of the cross groove joint was measured and compared with the calculated values.

The current battery carrier for commercial vehicles is made of steel and is designed to hold two batteries weighing approximately 80 kg to 100 kg. However, this battery carrier faces several issues including corrosion, chemical reactivity, high maintenance requirements and its heavy weight. To tackle these challenges, a fiber-reinforced composite battery carrier is designed and developed specifically for commercial vehicles. The objective is to identify a solution that can meet the performance requirements of both static and dynamic loading, thereby reducing the overall weight. The proposed composite battery carrier offers a lightweight design, requires minimal maintenance, possesses high tensile strength and stiffness and is corrosion and chemical resistant. Furthermore, it provides the flexibility to integrate battery cover locking arrangements for added convenience and security.

As the automotive industry focuses on fuel-efficient and eco-friendly vehicles along with reducing the carbon footprint, weight reduction becomes essential. Composite materials offer several advantages over metals, including lighter weight, corrosion resistance, low maintenance, longer lifespan, and the ability to customize their strength and stiffness according to specific loading requirements. This paper describes the design and development of the Rear Under Run Protection Device (RUPD) using composite materials. RUPD is designed to prevent rear under-running of passenger vehicles by heavy-duty trucks in the event of a crash. The structural strength and integrity of RUPD assembly are evaluated by applying loads and constraints in accordance with IS 14812:2005. The design objective was to reduce weight while maintaining a balance between strength, stiffness, weight, manufacturability, and cost.

The need for eco-friendly vehicle powertrains has increased drastically in recent years. The most critical component of an electric vehicle is the battery pack/cell. The choice of the appropriate cell directly determines the size, performance, range, life, and cost of the vehicle. Lithium-ion batteries with high energy density and higher cycle life play a crucial role in the progress of the electric vehicle. However, the packaging of lithium-ion cells is expected to meet lots of assembly demands to increase their life and improve their functional safety. Due to their low mechanical stability, the lithium-ion cell modules must have external pressure on the cell surface for improved performance. The cells must be stacked in a compressed condition to exert the desired pressure on the cell surface using compression foam/pads. The compression pads can be either packaged between each cell or once in every set of cells based on the cell assembly requirements.

Battery terminal voltage modelling is crucial for various applications, including electric vehicles, renewable energy systems, and portable electronics. Terminal voltage models are used to determine how a battery will respond under load and can be used to calculate run-time, power capability, and heat generation and as a component of state estimation approaches, such as for state of charge. Previous studies have shown better voltage modelling accuracy for long short-term memory (LSTM) recurrent neural networks than other traditional methods (e.g., equivalent circuit and electrochemical models). This study presents two new approaches – sequence training and data shuffling – to improve LSTM battery voltage models further, making them an even better candidate for the high-accuracy modelling of lithium-ion batteries. Because the LSTM memory captures information from past time steps, it must typically be trained using one series of continuous data.

As we move toward electrification in future mobility, weight and cost reduction continue to be priorities in vehicle development. This has led to continued interest in advanced molding processes and holistic design to enable polymer materials for demanding structural applications such as pickup truck beds. In addition to performance, it is necessary to continue to improve styling, functionality, quality, and sustainability to exceed customer expectations in a competitive market. To support development of a lightweight truck bed design, a cross-functional team objectively explored the latest materials and manufacturing technologies relevant to this application. In Phase 1 of this work, the team considered a variety of alternatives for each functional area of the bed, including thermoplastic and thermoset materials with a range of processing technologies.

Since entering the 21st century, the world has faced extremely serious environmental pollution and energy crises. In this context, new energy vehicles have been vigorously developed. Lithium-ion batteries have gradually become one of the most important energy sources for electric vehicles due to their excellent performance. State of charge (SOC) is one of the important indicators of the battery. Accurate estimation of SOC is of great significance to establishing a safe and accurate Battery management system (BMS). Among related methods for SOC estimation, observation-based methods have been widely used. However, this type of method has the disadvantages of being susceptible to disturbance and requiring high accuracy of the battery model. The traditional equivalent circuit model cannot meet the needs. This paper proposes a battery SOC estimation method based on LSSVM-UKF through research on lithium-ion battery modeling and SOC estimation methods.

Battery packs of electric vehicles are typically composed of lithium-ion batteries with aluminum and copper acting as cell terminals. These terminals are joined together in series by means of connector tabs to produce sufficient power and energy output. Such critical electrical and structural cell terminal connections involve several challenges when joining thin, highly reflective and dissimilar materials with widely differing thermo-mechanical properties. This may involve potential deformation during the joining process and the formation of brittle intermetallic compounds that reduce conductivity and deteriorate mechanical properties. Among various joining techniques, laser welding has demonstrated significant advantages, including the capability to produce joints with low electrical contact resistance and high mechanical strength, along with high precision required for delicate materials like aluminum and copper.

The study and application of Topology Optimization (TO) has experienced great maturity in recent years, presenting itself as a highly influential and sought-after design tool in both the automotive and aerospace industries. TO has experienced development from single material topology optimization (SMTO) to multi-material topology optimization (MMTO), where material selection is simultaneously optimized with material existence. Today, MMTO for standard structural optimization responses are well supported. An additional and vital response in the design of structures is that of stress. Stress-driven or stress-controlled optimization techniques for SMTO are well understood and have been well-documented, evidenced by both published works and its availability in multiple commercial solvers. However, its integration into MMTO frameworks has not yet achieved reliable levels of accuracy and flexibility.

In recent years, with the advent of the Fourth Industrial Revolution and the COVID-19 pandemic, people's lives worldwide have undergone significant changes. Additionally, the emergence of a new generation of consumers known as the millennial generation has led to a high demand for multipurpose family cars. The perspective is shifting towards choosing premium products that enhance the quality of life and pursue their own happiness and comfort through technology, rather than simply selecting a midsize SUV based on the increase in family size. We aim to meet the needs of these global customers by conducting research and developing various new features that were not previously available in midsize SUVs. In this study, we defined the actual target users for midsize SUVs and established UX concepts by analyzing their characteristics. Based on this, we employed an optimal design approach by analyzing the evaluation results by country for the various features implemented within the vehicle.

For the design optimization of the electric bus body frame orienting frontal crash, considering the uncertainties that may affect the crashworthiness performance, a robust optimization scheme considering tolerance design is proposed, which maps the acceptable variations in objectives and feasibility into the parameter space, allowing for the analysis of robustness. Two contribution analysis methods, namely the entropy weight and TOPSIS method, along with the grey correlation calculations method, are adopted to screen all the design variables. Fifteen shape design variables with a relatively high impact are chosen for design optimization.

This work aims to perform the optimization of the iron-aluminum lightweight body frame of a commercial electric bus orienting the static performance (e.g., strength and stiffness), side-impact safety, and possible reduction in mass. Firstly, both the static and side-impact finite element (FE) models are established for the electric bus body frame. The body frame is partitioned according to the deformation and the thickness of the square tube beams, and the contribution is analyzed by the relative sensitivity and the Sobol index methods. The thickness of the tube beams in the nine regions is selected as the design optimization variables. After data sampling by the Hamersley method and conducting design of experiments (DOE), the surrogate models for optimization are fitted by the least square method.

Carbon neutrality has become a significant target. One essential parameter regarding energy consumption and emissions is the mass of vehicles. Lightweight design improves the result of vehicle life cycle assessment (LCA), increases efficiency, and can be a step towards sustainability and CO2 neutrality. Weight reduction through structural optimization is a challenging task. Typical design development procedures have to be overcome. Instead of just a facelift or the creation of a derivative of the predecessor design, completely alternative design creation methods have to be applied. Automated structural optimization is one tool for exploring completely new design approaches. Different methods are available and weight reduction is the focus of topology optimization. This paper describes a fatigue life homogenization method that enables the weight reduction of vehicle parts. The applied CAE process combines fatigue life prediction and topology optimization.

The problem of keeping the stable starting performance of diesel engine under high altitude and low temperature conditions has been done a lot of research in the field of diesel engine, but there is a lack of research on extreme conditions such as above 2000 meters above sea level and below 0°C. Aiming at solving the cold start problem of diesel engine in extreme environment, a set of chamber system of cold start environment diesel engine was constructed to simulate environment of 3000m altitude and -20°C. A series of experimental research was conducted on cold start efficiency optimization strategy of a certain type of diesel engine at 3000m altitude and -20°C. In parallel, a diesel engine model was constructed through Chemkin to explore the influence of the three parameters of compression ratio, stroke length, and fuel injection advance angle on the first cold start cycle of diesel engine at 4000m altitude and -20°C.

Shell-and-tube heat exchangers, commonly referred to as radiators, are the most prevalent type of heat exchanger within the automotive industry. A pivotal goal for automotive designers is to increase their thermal effectiveness while mitigating pressure drop effects and minimizing the associated costs of design and operation. Their design is a lengthy and intricate process involving the manual creation and refinement of computer-aided design (CAD) models coupled with iterative multi-physics simulations. Consequently, there is a pressing demand for an integrated tool that can automate these discrete steps, yielding a significant enhancement in overall design efficiency. This work aims to introduce an innovative automation tool to streamline the design process, spanning from CAD model generation to identifying optimal design configurations. The proposed methodology is applied explicitly to the context of shell-and-tube heat exchangers, showcasing the tool's efficacy.

This study employs TRIZ, the Theory of Inventive Problem Solving, to optimize a 2.2-liter automotive diesel engine facing challenges from system technology upgrades in the fuel injection system. This system requires the common rail pump. Two pumps were chosen and based on fuel quantity balance (QB) and drive ratio, one pump was finalized as the technical option, and it was studied in a detailed manner to identify the improving and worsening parameters with the help of a contradiction matrix and the 40 TRIZ principle, which are the main core ideas of TRIZ. The worsening parameters (drive torque) are reduced by 21.36%, and the chain load in the 0.5% worn chain condition also fulfills the system requirement. The chosen pump is further studied. This also helped to identify and categorize the system components of the main engineering system into subsystems and supersystems.

In response to the stipulations of the Energy Policy and Conservation Act and the global momentum toward carbon mitigation, there has been a pronounced tightening of fuel economy standards for manufacturers. This stricter regulation is coupled with an accelerated transition to electric vehicles, catalyzed by advances in electrification technology and a decline in battery cost. Improvements in the fuel economy of medium- and heavy-duty vehicles through electrification are particularly noteworthy. Estimating the magnitude of fuel economy improvements that result from technological advances in these vehicles is key to effective policymaking. In this research, we generated vehicle models based on assumptions regarding advanced transportation component technologies and powertrains to estimate potential vehicle-level fuel savings. We also developed a systematic approach to evaluating a vehicle’s fuel economy by calibrating the size of the components to satisfy performance requirements.