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Multi-Objective Optimization Under the Hood: Engine Calibration via Metaheuristics and Probabilistic Methods
(2025) Borg, Sara; Hui, Victor
The automotive industry faces the complex task of optimizing engine performance across diverse and often competing metrics, including fuel consumption and emissions. To effectively address this challenge and manage the necessary trade-offs, accurate engine calibration is essential. This thesis investigates the application of optimization methods, specifically Genetic Algorithms (GA) and Bayesian Optimization (BO), as a promising solution for engine calibration. Single-objective optimization targets the best solution for one goal, while multi-objective optimization balances trade-offs between conflicting goals to approximate the Pareto front, the set of optimal solutions where no objective can be improved without worsening another. This work explores both single-objective and multi-objective optimization implementations for GA and BO. In addition, a hybrid approach combining BO followed by GA is proposed for multi-objective optimization. The methods were evaluated in an experimental study. In the single-objective case, both GA and BO outperformed established internal benchmark values (provided by Volvo). For multi-objective optimization, GA, BO, and the hybrid method also achieved superior results. Across both single-objective and multi-objective problems, BO consistently delivered the best performance. These findings demonstrate that GA, BO, and the hybrid approach are viable strategies for engine calibration and provide a strong foundation for the development of more specialized calibration methods.
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Extensions of Constant Proportion Portfolio Insurance using the Geometric Ornstein-Uhlenbeck process and the Chan-Karolyi-Longstaff-Sanders process
(2026) Bengtsson, Jonathan
We investigate performance of the Constant Proportion Portfolio Insurance (CPPI) strategy and compare it with two of its extensions: Time Invariant Portfolio Protection (TIPP) and Exponential Proportion Portfolio Insurance (EPPI). In order to do this, we model a risky asset (a stock or an index) using a Geometric Ornstein-Uhlenbeck process, and estimate its parameters using the likelihood ratio method with historical price data. We model a non-risky asset (a zero-coupon bound) using a Chan-Karolyi-Longstaff-Sanders process and estimate its parameters using the maximum likelihood method where we approximate the transition probability density function using a Hermite expansion. We find that both extensions of the CPPI improve performance in different ways. The resulting distribution of simulated portfolio outcomes for the TIPP strategy has a lighter tail compared to the CPPI case, and the risk of loss is lower (this is also true compared to the EPPI strategy, but to a smaller degree). The EPPI strategy translates the distribution of simulated portfolio outcomes to the right, so that EPPI performs better than CPPI (and TIPP) in terms of both mean and median.
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Survey on seamless on-board and cloud connectivity for transport missions
(2026) Uzair, Muhammad
The reliable connectivity required for mission-critical transport systems, such as autonomous driving, remains a challenge in areas with limited terrestrial network coverage. Non-Terrestrial Networks (NTNs), particularly Low Earth Orbit (LEO) satellites, have emerged as a promising solution to fill this gap. The study employs a comprehensive MATLAB-based simulation framework informed by 3GPP TR 38.811 and ITU-R channel models. The methodology involves a systematic approach where free-space path loss, atmospheric attenuation, Doppler shift, and environmental fading are integrated into a complete link budget. The primary contribution of this research is its integrated analysis of these factors specifically for vehicular links, providing a unified assessment of performance through key metrics including Bit Error Rate (BER) versus Carrier-to-Noise Ratio (CNR), BER versus Eb/N0, throughput, latency, and Doppler shift. The results demonstrate that elevation angle is the dominant factor governing link quality. Performance improves dramatically from near-unusable conditions at 10◦ to reliable, near-error-free operation (BER < 10−6) at 90◦ elevation. A critical finding is the establishment of a universal CNR threshold of approximately 15 dB for reliable operation. The analysis reveals a fundamental design trade-off: Ka-band offers higher throughput, while S-band provides robustness against impairments. Latency analysis confirms that LEO systems can meet the delay requirements for connected transport services. This study concludes that LEO-based NTNs are a viable complementary technology for intelligent transportation systems. The findings provide a clear framework for system design, highlighting the critical importance of elevation-aware planning and strategic frequency band selection.
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Optimizing Market Engagement: Strategic Models for District Heating Companies’ Participation in Electricity Markets
(2026) Burman, Jacob
District heating companies in Sweden are presented with opportunities to participate in newer electricity markets beyond the spot market, such as intraday and ancillary markets. However, navigating these markets requires advanced and complex strategies due to the varying market rules, market timings, and operational constraints of combined heat and power units. This thesis develops a flexible mixed-integer linear programming model to optimize multi-market participation for district heating companies. The model integrates the market rules and all possible operational constraints to determine profit-maximizing strategies across electricity markets. Simulations using historical data showed that there is great value in participating in one additional ancillary market, with increases in profit ranging from 35% to 1100% depending on season. We also noticed that participation in more than two to three markets yields less profit increase, but on the other hand an increased complexity for daily operations in the district heating companies, suggesting that two to three markets is a balanced amount of participation. Since the technical qualifications for the ancillary markets are tough, many district heating companies might not have the opportunity to participate in more than one or two such markets, which strengthens this result. A comparison with Utilifeed’s baseline model highlights the accuracy of our model and the added value of incorporating it in Utilifeed’s model. The results show the importance of enabling district heating companies to navigate the complexity of multi-market participation, improving profitability while supporting the grid balancing.