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The ongoing energy transition will have a profound impact on future mobility, with electrification playing a key role. Battery electric vehicles (EVs) are the dominant technology, relying on the conversion of alternating current (AC) from the grid to direct current (DC) to charge the traction battery. This process involves power electronic components such as rectifiers and DC/DC converters operating at high switching frequencies in the kHz range. Fast switching is essential to minimize losses and improve efficiency, but it might also generate electromagnetic interferences (EMI). Hence, electromagnetic compatibility (EMC) testing is essential to ensure reliable system operations and to meet international standards. During DC charging, the AC/DC conversion takes place off-board in the charging station, allowing for better cooling and larger components, resulting in increased power transfer, currently up to 350 kW.

When using "green" hydrogen, fuel cell technology plays a key role in emission-free mobility. A powertrain based on fuel cells (FC) shows its advantages over battery-electric powertrains when the requirement profile primarily demands high performance over a longer period of time, high flexible availability and short refueling times. In addition, FC achieves higher effi-ciencies than the combustion of hydrogen in a gas engine, meaning that the chemical energy is used more efficiently than with established combustion engines. When using FC technology, numerous companies in Baden-Württemberg can contribute their specific expertise from the traditional automotive construction and supplier business. This includes auxiliary units in the air (cathode) and hydrogen (anode) path, such as the air compressor, the H2 recycling pump, humidifier, cooling system, power electronics, valve and pressure tank technology as well as components of the fuel cell stack itself.

Previous studies have shown that dosing AdBlue into the exhaust system of diesel engines to reduce nitrogen oxides can lead to an increase in the number of particles (PN). In addition to the influencing factors of exhaust gas temperature, exhaust gas mass flow and dosing quantity, the dosed medium itself (AdBlue) is not considered as a possible influence due to its regulation in ISO standard 22241. However, as the standard specifies limit value ranges for the individual regulated properties and components for newly sold AdBlue, in reality there is still some margin in the composition. This paper investigates the particle number increase due to AdBlue dosing using several CPCs. The increase in PN is determined by measuring the number of particles after DPF and thus directly before dosing as well as tailpipe. Several AdBlue products from different sources and countries are measured and their composition is also analyzed with regard to the limit values regulated in the standard.

The modern automotive industry is facing challenges of ever-increasing complexity in the electrified powertrain era. On-board diagnostic (OBD) systems must be thoroughly validated and calibrated through many iterations to function effectively and meet the regulation standards. Their development and design process are more complex when prototype hardware is not available and therefore virtual testing is a prominent solution, including Software-in-the-loop (SiL) and Hardware-in-the-loop (HIL) simulations. Virtual prototype testing relying on real-time simulation models is necessary to design and test new era’s OBD systems quickly and in scale. The new fuel cell powertrain involves new and preciously unexplored fail modes. To make the system robust, simulations are required to be carried out to identify different fails.

This research aims to develop an inverse control method capable of adaptively simulating dynamic models of car subsystems in the rig-test condition. Accurate simulation of the actual vibration conditions is one of the most crucial factors in realizing reliable rig-test platforms. However, most typical rig tests are conducted under simple random or harmonic sweep conditions. Moreover, the conventional test methods are hard to directly adapt to the actual vibration conditions when switching the dynamic characteristics of the subsystem in the rig test. In the present work, we developed an inverse controller to adaptively control the vibration exciter referring to the target vibration signal. An adaptive LMS filter, employed for the control algorithm, updated the filter weights in real time by referring to the target and the measured acceleration signals.

Vehicles equipped with articulated steering systems have advantages such as low energy consumption, simple structure, and excellent maneuverability. However, due to the specific characteristics of the system, these vehicles often face challenges in terms of lateral stability. Addressing this issue, this paper leverages the precise and independently controllable wheel torques of a hub motor-driven vehicle. First, an equivalent double-slider model is selected as the dynamic control model, and the control object is rationalized. Subsequently, based on the model predictive control method and considering control accuracy and robustness, a weight-variable adaptive model predictive control approach is proposed. This method addresses the optimization challenges of multiple systems, constraints, and objectives, achieving adaptive control of stability, maneuverability, tire slip ratio, and articulation angle along with individual wheel torques during the entire steering process of the vehicle.

Validation plays a crucial role in any Electronic Development process. This is true in the development of any automotive Electronic Control Unit (ECU) that utilizes the Automotive V process. From Research and Development (R&D) to End of Line (EOL), every automotive module goes through a plethora of Hardware (HW) and Software (SW) testing. This testing is tedious, time consuming, and inefficient. The purpose of this paper is to show a way to streamline validation in any part of the automotive V process using Python as a driving force to automate and control Hardware-in-the-loop (HIL) / Model-in-the-loop (MIL) / Software-in-the-loop (SIL) validation. The paper will propose and outline a framework to control test equipment, such as power supplies and oscilloscopes, load boxes, and external HW. The framework includes the ability to control CAN communication signals and messages.

This paper introduces reduced-order modeling techniques with Artificial Intelligence (AI) for Model-Based Development (MBD). In vehicle development, detailed physical models are replaced by reduced-order models (ROM) to expedite simulations. With recent advancements in AI-based reduced-order modeling, it is expected that modeling work will become more efficient, leading to reduced simulation times. However, the range of simulations (Model-in-the-Loop Simulation - MILS, Hardware-in-the-Loop Simulation - HILS, bench-system) compatible with ROM is limited. To overcome this limitation, this study leverages the ONNX format (Open Neural Network Exchange), a universally supported format among machine learning frameworks, and the Functional Mock-up Interface (FMI), a standard interface format for simulation tools, to enable general-purpose embedded technology with ROM. This study employs a vehicle model in engine surge simulations to validate AI-based reduced-order modeling for MBD.

Hardware-in-the-loop (HIL) testing is part of automotive V-design which is commonly used in automotive industries for the development of Electronic Control Unit (ECU). HIL test platform provides the capacity to test the ECU in a controlled environment even with scenarios that would be too dangerous or impractical to test on real situation, also the ECU can be tested even before the actual plant under building. This paper presents a HIL test platform for the validation of a seat ECU. The HIL platform can also be used for control and diagnostics algorithm development. The HIL test platform consists of three parts: a real time target machine (dSPACE SCALEXIO AutoBox), an ECU (Magna Seating M12 Module), and a signal conditioning unit (Load Box). The ECU produces the control commands to the real-time target machine through load box. The real time target machine hosts the plant model of the power seat which includes the kinematics and dynamics of the seat movements.

The paper presents a robust adaptive control technique for precise regulation of a port fuel injection + direct injection (PFI+DI) system, a dual fuel injection configuration adopted in modern gasoline engines to boost performance, fuel efficiency, and emission reduction. Addressing parametric uncertainties on the actuators, inherent in complex fuel injection systems, the proposed approach utilizes an indirect model reference adaptive control scheme. To accommodate the increased control complexity in PFI+DI and the presence of additional uncertainties, a nonlinear plant model is employed, incorporating dynamics of the exhaust burned gas fraction. The primary objective is to optimize engine performance while minimizing fuel consumption and emissions in the presence of uncertainties. Stability and tracking performance of the adaptive controller are evaluated to ensure safe and reliable system operation under various conditions.

This paper details the advancements and outcomes of the NEXTCAR (Next-Generation Energy Technologies for Connected and Automated on-Road Vehicles) program, an initiative led by the Advanced Research Projects Agency-Energy (ARPA-E). The program focusses on harnessing the full potential of Connected and Automated Vehicle (CAV) technologies to develop advanced vehicle dynamic and powertrain control technologies (VD&PT). These technologies have shown the capability to reduce energy consumption by 20% in conventional and hybrid electric cars and trucks at automation levels L1-L3 and by 30% L4 fully autonomous vehicles. Such reductions could lead to significant energy savings across the entire U.S. vehicle fleet.

Electro-Mechanical Braking (EMB) system, which completely abandons the traditional hydraulic device, realizes complete human-vehicle decoupling and integrates various functions without adding additional accessories, could meet the requirements of the future intelligent driving technology for high-quality braking control. However, there are significant internal interference of nonlinear characteristics such as mechanical friction and system variable stiffness during the actual working process of EMB, and these make the accuracy and rate of the clamping force control decline. This paper proposes a precise clamping force control strategy for EMB based on nonlinear characteristics compensation. First, we systematically analyze the working principle of EMB, and establish the mathematical model of EMB system including motor, transmission mechanism and friction. At the same time, some typical experiments are designed to identify internal parameters of friction model.

The steer-by-wire (SBW) system, an integral component of the drive-by-wire chassis responsible for controlling the lateral motion of a vehicle, plays a pivotal role in enhancing vehicle safety. However, it poses a unique challenge concerning steering wheel return control, primarily due to its fundamental characteristic of severing the mechanical connection between the steering wheel and the turning wheel. This disconnect results in the inability to directly transmit the self-aligning torque to the steering wheel, giving rise to complications in ensuring a seamless return process. In order to realize precise control of steering wheel return, solving the problem of insufficient low-speed return and high-speed return overshoot of the steering wheel of the SBW system, this paper proposes a steering wheel active return control strategy for SBW system based on the backstepping control method.

The powertrain electrification is currently not only taking place in public road mobility vehicles, but is also making its way to the racetrack, where it’s driving innovation for developments that will later be used in series production vehicles. The current development focus for electric vehicles is the balance between driving power, range and weight, which is given even greater weighting in racing. To redefine the current limits, IAV developed a complete e-powertrain for a racing MX motorcycle and integrated it into a real drivable demonstrator bike. The unique selling point is the innovative direct phase-change cooling (PCC) of the three-phase e-motor and its power electronics, which enables significantly increased continuous power (Pe = 40 kW from 7,000 rpm to 9,000 rpm) without thermal power reduction. The drive unit is powered by a replaceable Lithium-Ion round cell battery (Ubat,max = 370V) with an energy storage capacity of Ebat = 5 kWh.

When designing an electric vehicle (EV) traction system, overcoming the issues arising from the variations in the battery voltage due to the state of charge (SoC) is critical, which otherwise can lead to a deterioration of the powertrain energy efficiency and overall drive performance. However, systems are typically documented under fixed voltage and temperature conditions, potentially lacking comprehensive specifications that account for these variations across the entire range of the vehicle operating regions. To tackle this challenge, this paper seeks to adjust an optimal DC-link voltage across the complete range of drive operating conditions by integrating a DC-DC converter into the powertrain, thereby enhancing powertrain efficiency. This involves conducting a comprehensive analysis of power losses in the power electronics of a connected converter-inverter system considering the temperature variations, along with machine losses, accounting for variable DC-link voltages.

The suspension system plays a crucial role in mitigating vehicle vibration, enhancing passenger comfort, and improving driving handling stability. While many mechanical experimental platforms exist for testing suspension system performance, they often need high costs and precision requirements. In the field of modern industrial product design, hardware-in-the-loop (HIL) simulation has become an invaluable tool. Electrically interconnected suspension (EIS) is a novel type of interconnected suspension by connecting various suspensions in an electrical way. The novel EIS avoids many drawbacks of traditional interconnected suspensions. The EIS is usually composed of electromagnetic motors and electrical networks (EN). By designing the structure of the EN reasonably, the EIS system can achieve decoupling control in multiple vibration modes. This paper introduces an HIL experimental platform established for a half-car EIS system based on an NI Compact RIO 9049.

The EPB (Electric Parking Brake) system is divided into two parts based on VDA305-100 recommendation (German Association of the Automotive Industry, VDA). One part of the EPB system contains the parking brake actuator, caliper, and actuation logic (parking brake controller, PBC). The second part of the EPB system is called to the HOST which contains the EPB power electronics, necessary peripherals and controls the functions that the driver can experience. According to VDA305-100, the PBC is responsible for recognition of a fault in the parking brake actuator based on the measured values transmitted from the HOST such as EPB motor voltage and current. Due to mechanical fault injection limitations, failsafe tests require physically electrical emulation caused by parking brake actuator faults to verify the parking brake actuator fault detection and management algorithm.

Simulators are essential part of the development process of vehicles and their advanced functionalities. The combination of virtual simulator and Hardware-in-the-loop technology accelerates the integration and functional validation of ECUs and mechanical components. The aim of this research is to investigate the benefits that can arise from the coupling of a steering Hardware-in-the-loop simulator and an advanced multi-contact tire model, as opposed to the conventional single-contact tire model. On-track tests were executed to collect data necessary for tire modelling using an experimental vehicle equipped with wheel force transducer, to measure force and moments acting on tire contact patch. The steering wheel was instrumented with a torque sensor, while tie-rod axial forces were quantified using loadcells. The same test set has been replicated using the Hardware-in-the-loop simulator using both the single-contact and multi-contact tire model.

Mechanical drawing plays an important role in managing, designing and implementing engineering projects, especially in the field of the automotive industry. The need for accuracy in element design and manufacturing is greater now than ever before in engineering industries. In order to increase accuracy, the part design and function must be clearly communicated between the design engineer and the manufacturing technicians, especially in automotive industry and feeder industries projects. Geometric Dimensions and Tolerances (GD&T) system of elements determines the quality, importance and price of the designed product. The standard used in the United States to define GD&T methodology is ASME Y14.5-2009 while the standard used in Europe is ISO 1101-2017. This article discussed the importance of using GD&T system including the types of geometrical features, limitations and accuracy, datum references frame and feature control frame to handle these symbols seamlessly.

With the rapid advancement in intelligent vehicle technologies, comprehensive environmental perception has become crucial for achieving higher levels of autonomous driving. Among various perception tasks, monitoring road types and evenness is particularly significant. Different road categories imply varied surface adhesion coefficients, and the evenness of the road reflects distinct physical properties of the road surface. This paper introduces a two-stage road perception framework. Initially, the framework undergoes pre-training on a large annotated drivable area dataset, acquiring a set of pre-trained parameters with robust generalization capabilities, thereby endowing the model with the ability to locate road areas in complex regions.