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Senast publicerade

Utveckling av roterande testrigg för ADAS-ljustester
(2026) Alfredsson, Johannes; Nenov, Plamen
Inom fordonsindustrin finns ett stort behov av noggranna och effektiva testmetoder för att utvärdera avancerade strålkastarsystem (ADAS). Detta examensarbete har genomförts i samarbete med Volvo Cars vid AstaZero och syftar till att utveckla en automatiserad lösning för förflyttning och positionering av en befintlig testrigg för ljustester. Arbetet har omfattat en systematisk produktutvecklingsprocess, där problemidentifiering, kravspecifikation, konceptframtagning, konstruktion och testning har genomförts. Flera koncept togs fram och utvärderades utifrån kriterier såsom precision, repeterbarhet och praktisk genomförbarhet. Under projektet genomfördes beräkningar och praktiska tester för att säkerställa systemets funktion, där fokus låg på att uppnå god linjering, minimera vibrationer och säkerställa mekanisk stabilitet. Resultatet visar att den utvecklade lösningen kan minska behovet av manuellt arbete, förbättra ergonomin samt bidra till en mer effektiv testprocess. Samtidigt identifierades begränsningar kopplade till tid och resurser, vilket innebar att vissa avancerade funktioner, såsom automatisk positionsloggning och fullständig mjukvaruintegration, inte kunde implementeras. Slutsatsen är att den framtagna lösningen uppfyller projektets huvudsakliga mål och har potential att vidareutvecklas till ett mer automatiserat och integrerat testsystem. Arbetet visar även vikten av att kombinera teoretiska lösningar med praktisk genomförbarhet i ett ingenjörsmässigt utvecklingsarbete.
Precision Exploration and Underflow Mitigation for BAPS Digital Predistortion
Duan, Yiran
Digital predistortion (DPD) is widely used to compensate for the nonlinear be haviour of radio-frequency power amplifiers (PAs). The basis-propagating selection (BAPS) algorithm builds DPD models by reusing previously computed basis functions, making it attractive for hardware implementation. However, when reduced precision floating-point arithmetic is used, these sequential multiplication chains create dynamic range challenges. This thesis investigates how the number of mantissa bits (t), the number of exponent bits (w), and the number of BAPS basis functions (R) affect DPD linearisation performance, evaluated using normalised mean square error (NMSE) and adjacent channel power ratio (ACPR), and hardware cost. A Python-based simulation framework using the APyTypes library is developed to evaluate custom floating-point configurations and generate test vectors for register-transfer-level (RTL) verification. A joint sweep of R and t produces a two dimensional NMSE heatmap. For the selected BAPS sequence and test case, the performance plateau is reached at R = 6 and t = 7; larger values give no measurable NMSE improvement. This extends the fixed-R mantissa-width result reported in prior work by showing the joint effect of R and t. Reducing t from 23 to 7 reduces the synthesised area by approximately 78% without measurable loss in DPD linearisation performance. The exponent-width study shows that, without scaling, intermediate Type II products underflow at w = 5, removing important basis functions and making the predistorter ineffective. This thesis therefore uses power-of-two scaling, which raises these products using exponent shifts only, without additional floating-point multipliers. At t = 7, the scaled (w,t) = (5,7) design recovers performance close to the reference level and uses 5.9% less area than the scaled (6,7) design. At w = 4, the model coefficients underflow, so w = 5 is the practical lower bound for the studied signal and PA operating point. The configuration (w,t) = (5,7) with power-of-two scaling reduces the synthesised total area to 21% of the single-precision baseline, while meeting the common 5 ns clock-period constraint used for the synthesis of all configurations, including the single-precision baseline. Selected configurations are also validated using the RF WebLab measurement platform and PA gate-voltage robustness tests. The results show that reduced-precision BAPS DPD can provide substantial hardware savings while maintaining linearisation performance close to the full-precision reference.
Development of Acoustic Metamaterial Vibrational Shields for Application at Cryogenic Temperatures
(2026) Carlsson, Einar
Phononic crystals and acoustic metamaterials are prominent areas of research in the fields of acoustics and solid mechanics. These materials allow for the manipulation and suppression of elastic waves, for example sound waves in air or vibrational waves in solids. In particular, the mitigation of vibrational waves is of interest, with even small vibrations potentially causing noise in some low temperature experiments. In this thesis phononic crystals are presented as a method of vibration isolation at cryogenic temperatures. The design and development of the acoustic metamaterials was guided by numerical simulations performed using the finite element method (FEM), where band structures were optimized and designed for a suitable geometry and material composition. Two of the simulated designs were fabricated with acrylic plastic and characterized using optical interferometry. By comparing the motion of the metamaterials with a reference bulk material the attenuation caused by it could be determined, resulting in an upper bound of 15 to 20 dB in attenuation across a frequency interval of roughly 7.0 - 11.0 kHz. Simulated metamaterials show encouraging results with band gap generation at frequencies below 4 kHz through careful considerations of the utilised materials. Further work is required to realise the experimental implementation, with reducing the noise floor of the interferometry measurements of particular importance, along with producing and testing more samples.
World Model Online Evaluation
(2026) Dalevi, Alice; Sjöberg, Tina
To further advance the development of Advanced Driver Assistance Systems (ADAS), ensuring a robust learning-based perception system is essential. One approach to achieving this is the collection of diverse and informative data for training perception models. Active learning is based on the principle that exposing models to previously unseen or challenging data improves their performance. To facilitate this, this thesis evaluates several motion-based methods for detecting inconsistencies in the behavior of perception systems. These methods aim to identify scenarios in which the system performs poorly, enabling targeted data collection. The results show that, for a learning-based perception system, more complex methods generally yield better performance. In particular, Factor Graph Optimization with a Coordinated Turn motion model demonstrates the greatest potential, which may be attributed to the complex and dynamic behavior of objects in traffic environments. Furthermore, the findings suggest that future work exploring more advanced motion models, as well as combinations of multiple models, is a promising direction for improving perception system performance.
Vertical integration in energy system modelling Understanding the effects of European energy trading on the Swedish energy system
(2026) Roslund, Leo; Jonsson Rosenberg, Viktor
Understanding a country’s future energy system requires modelling, yet national energy system models typically treat countries as isolated systems, ignoring cross-border interdependencies. Fully resolving this limitation is computationally intractable, as adequately representing neighbouring countries requires their neighbours in turn, rapidly producing models too large to solve. This project addresses this by developing a vertical integration methodology that couples a national sub-model with a surrounding macro-level model. Cross-border trade flows are extracted from the macro-level model and applied as boundary conditions in the sub-model, allowing the national system to respond to external energy market pressures without requiring a fully resolved continental model. The methodology is implemented within the GENeSYS-MOD framework and evaluated through a Swedish case study, using a newly constructed dataset divided into Sweden’s four electricity bidding zones. The results demonstrate that vertical integration fundamentally reshapes Sweden’s optimal energy configuration in ways an isolated model cannot capture. Hydrogen export demand to Finland emerges as the dominant driver, cascading through the power system and redirecting electricity away from domestic industry, slowing its electrification. Access to imported natural gas further reinforces this pattern, as fossil-fired heating becomes more competitive than electric alternatives. Although net emissions remain comparable between the models, the vertically integrated model shifts toward a greater dependency on carbon capture technologies rather than emissions reduction at source. The sub-model also exposed a spatial resolution mismatch: trade patterns optimised at the European level can produce infrastructure investments that are impractical at the national scale. The study highlights that what is optimal from a European perspective may not align with national climate goals, a tension that isolated national models cannot reveal. Addressing this through more sophisticated vertical integration methodologies represents an important direction for future research.