Marco Günther

With the increasing complexity of electrical and electronic (E/E) components in modern powertrains, functional safety requires more systematic assessment methods. This paper presents a simulation-based approach for automated Hazard Analysis and Risk Assessment (HARA) of battery electric vehicles in accordance with ISO 26262. The method combines operational-situation parameters, including vehicle speed, road surface, vehicle gap, and road inclination, to define a structured set of hazardous events. Severity, Exposure, and Controllability are evaluated using rule-based criteria, including a dedicated Controllability rule set for longitudinal motion hazards. Quantitative erroneous acceleration and deceleration thresholds associated with different ASILs are derived using a bisection search algorithm, enabling quantifiable and testable safety goals. Comparison with manual HARA reveals systematic biases: low speed does not necessarily imply improved Controllability due to shorter vehicle gaps, while Severity may be underestimated at low speeds because of high instantaneous electric-machine torque. The maximum ASIL is often identified similarly by simulation and experts, whereas lower-ASIL hazardous events may lack consistency and coverage in manual HARA. As a practical application, the approach can be integrated into existing automotive safety workflows as a HARA support tool, improving the consistency of lower-ASIL events while allowing engineers to focus on maximum ASIL cases.

Model Predictive Control (MPC) has emerged as a promising approach for energy management in hybrid electric vehicles, enabling predictive optimization of powertrain operation. The energy management problem in parallel hybrid powertrains constitutes a Mixed-Integer Nonlinear Programming (MINLP) problem, combining continuous decision variables such as torque distribution with discrete decisions including engine on/off states and clutch engagement. This problem structure presents distinct challenges for different optimization approaches. Gradient-based methods such as Sequential Quadratic Programming (SQP) solve continuous, differentiable optimization problems and require auxiliary methods to handle integer variables, while metaheuristic approaches such as Genetic Algorithms (GA) can handle the mixed-integer structure directly at the cost of increased computational effort. This study presents a systematic comparison between GA and SQP as optimization solvers within an MPC framework for a P1P3 parallel hybrid powertrain. A multi-objective cost function is formulated to simultaneously optimize system efficiency, battery state of charge management, and noise emissions. Both approaches are evaluated across the WLTC as well as a real-world RDE scenario. On the WLTC, both MPC approaches reduce fuel consumption by 0.5–1.0% and improve system efficiency by 3.7–4.6% compared to a state-of-the-art deterministic reference strategy optimized for fuel consumption. At the same time, both approaches additionally achieve substantial reductions in noise emissions compared to the deterministic reference, which was not optimized for acoustic behavior. On both cycles, the GA-based MPC achieves favorable performance compared to SQP, with the performance gap widening from the WLTC to the RDE cycle. Both methods achieve real-time capability, yet SQP reduces computational time by a factor of four compared to GA. As long as computational resources in automotive ECUs remain constrained, this efficiency advantage positions gradient-based optimization for series production applications, whereas metaheuristic methods offer greater flexibility for concept development stages with relaxed real-time requirements. The findings contribute to the understanding of optimization algorithm selection for MINLP energy management problems in hybrid electric vehicles.

Many cities are still struggling to comply with current air quality regulations. Road transport is usually a significant source of NOx emissions, especially in urban areas. Therefore, NOx from road vehicles needs to be further reduced below current standards to ultra-low or even zero-impact levels. In a novel, holistic powertrain design approach, this paper presents powertrain solutions to achieve zero-impact NOx emissions with an N1 class III diesel light commercial vehicle. The design is based on a compliance test matrix consisting of six real-world scenarios that are critical for emissions and air quality. As a design baseline, a vehicle concept meeting the emission requirements as set out in the European Commission’s 2022 Euro 7 regulation proposal is used. The baseline vehicle concept can achieve zero-impact NOx emissions in 67% of these scenarios. To achieve zero-impact NOx emissions in all scenarios, further advanced emission solutions are mandatory. In congested urban areas, the use of an exhaust gas aftertreatment system preheating device with at least 20 kW of power for 1 min is required. In high-traffic highway situations, an underfloor SCR unit with a minimum volume of 12 l or the restriction of the maximum vehicle speed at 130 km/h is required.

The automotive industry faces development challenges due to emerging technologies, regulatory demands, societal trends, and evolving customer mobility needs. These factors contribute to a wide range of vehicle variants and increasingly complex powertrains. The layout of a vehicle is usually based on standardized driving cycles such as WLTC, gradeability, acceleration test cases, and many more. In real-world driving cycles, however, this can lead to limitations under certain boundary conditions. To ensure that all customer requirements are met, vehicle testing is conducted under extreme environmental conditions, e.g., in Sweden or Spain. One way to reduce the development time while ensuring high product quality and cost-effectiveness is to use model-based methods for the comprehensive design of powertrains. This study presents a layout methodology using a top-down approach. Initially, powertrain-relevant requirements for an exemplary target customer are translated into a specification sheet with specific test cases. An overall vehicle model with detailed thermal sub-models is developed to evaluate the different requirements. A baseline design for a C-segment plug-in hybrid vehicle was developed as part of the FVV research project HyFlex-ICE using standardized test cases, highlighting the influence of customer profiles on the design outcome through varying weighting factors. The target customer’s design is analyzed in four real driving scenarios, considering variations in parameters such as the ambient temperature, traffic, driver type, trailer pulling, and battery state-of-charge, to assess their influence on the target variables. In the next step, the potential of hardware technologies and predictive driving functions is examined in selected driving scenarios based on the identified constraints of the baseline design. As a result, four application-specific technology packages (Cost neutral, Cold country, Hot country, and Premium) for different customer requirements and sales markets are defined, which, finally, demonstrates the applicability of the holistic methodology.

The improvement of air quality requires a further reduction of pollutant emissions, especially in urban areas. The Euro 7 regulations aim at the development of a new generation of internal combustion engine vehicles capable of achieving ultra-low pollutant emissions under demanding, real-world operating conditions. They introduce new technical challenges in the holistic design of a vehicle’s powertrain and emission control system. To identify these, four real-world Euro 7 driving scenarios are investigated, covering demanding urban, highway and mountain driving situations. Technical solutions are then presented to address these challenges and ensure compliance with the Euro 7 emission requirements as set out in the latest regulation proposal of the European Commission. The study focuses on the NOx emissions of an N1 Class III light commercial vehicle with 3.5 t mass and a P2 diesel mild-hybrid powertrain. To ensure emission compliance, a Euro 6e exhaust gas aftertreatment system with enlarged catalysts is combined with NOx raw emission improvements. For low-load cold starts, a 4-kW electric heater in the exhaust system is considered in addition to a 2-l DOC and a 6-l DPF with SCR coating. For high-load cycles with high raw emissions, a 10-l underfloor SCR is considered to ensure the necessary deNOx performance.

Understanding cycle-to-cycle variations (CCV) is of practical importance for the combustion of fossil and renewable fuels, as increasingly stringent emission regulations require reductions in the negative effects of such variations. The subject of this study is the flow around inlet valves, since oscillations of such inlet flows affect the flow structure in the cylinder and are thus one of the causes of CCV. To this end, a parametric analysis of the influences of the mass flow rate and valve lift of two parallel engine intake valves on the flow structures is performed. This follows on from an earlier similar study where the flow around a single intake valve was investigated. To analyse the flow behaviour and, in particular, the interactions of the flow leaving these two valves, an optical test rig for 2D particle image velocimetry (PIV) and a large eddy simulation (LES) are used. Proper orthogonal decomposition (POD), together with a quadruple decomposition and the Reynolds stress transport equations, are used to study the turbulence phenomena. The PIV and LES results are in good agreement with each other. The detailed LES analysis of the flow structures shows that, for small valve lifts, the flow separates along the whole perimeter of the intake valve, and for larger valve lifts, the flow escapes only to one side. This is, for combustion engines with the tumble concept, the stage at which the tumble movement develops. Moreover, the flow structures are strongly influenced by the valve lift, while they are unaffected by the variation in the mass flow. The turbulent kinetic energy in the flow field increases quadratically with a decreasing valve lift and increasing mass flow. The large, high-energetic flow structures are particularly dominant near the jet, and the small, low-energetic structures are homogeneously distributed within the flow field. The specific Reynolds stress transport equation shows the limitations of two-dimensionality and large timesteps in the PIV results and the limitations of the LES model.