As the energy source of new energy vehicles, the high-voltage battery pack fundamentally determines driving range, service life, and operational safety. Lithium-ion batteries have been widely adopted in vehicles due to their high energy density and long cycle life. However, temperature significantly affects the performance of these batteries — both excessive heat and extreme cold can degrade performance and compromise safety. Therefore, it is critical to control the temperature of the high-voltage battery within its optimal operating window to ensure reliable operation under a wide range of driving conditions. In this study, I designed a side-mounted liquid cooling plate with staggered rib and groove structures and performed optimization by combining numerical simulation, single-factor analysis, and multi-objective optimization methods. My work focused on improving the cooling performance and temperature uniformity of the high-voltage battery system without substantially increasing pumping power. The most significant temperature constraint for a high-voltage battery module is to maintain the maximum temperature below 35°C and the module temperature difference within 5°C during normal operation. At ambient temperature of 25°C, a 2C discharge with no active cooling can push the cell temperature to over 54°C, which is far beyond the recommended limit. Hence, efficient liquid cooling for the high-voltage battery is indispensable.
In this research, I first investigated the thermal properties of a lithium-ion cell. I conducted a hybrid pulse power characterization (HPPC) test to measure the internal resistance under various state-of-charge levels and then fitted the heat generation rate as a function of discharge time. The cell’s anisotropic thermal conductivity and volumetric heat capacity were calculated from its layered structure. I then carried out temperature rise experiments on the cell during 0.5C, 1C, and 2C discharges and compared the measured surface temperatures with a three-dimensional thermal simulation. The simulation results agreed closely with the test data, with a maximum deviation under 8% across the considered discharge rates, verifying the reliability of my thermal model for building a battery pack simulation.
To determine an appropriate cooling arrangement for the high-voltage battery pack, I built a single-layer pack model comprising eight cells, nine cooling plates, and thermal interface pads. I simulated two different cooling plate positions: one with the plate under the cells (bottom cooling) and the other with plates placed between the cells (side cooling). Both configurations used identical accordion-style flow channels, the same inlet/outlet arrangement, the same total coolant volume flow rate of 21.78 L/min, and the same inlet temperature of 25°C. At the end of a 2C discharge, the bottom-cooled pack reached a maximum temperature of 39.67°C, with a pack-level temperature difference of 13.27°C and a cell-level maximum difference of 12.15°C. The side-cooled design produced substantially better results, with the maximum temperature reduced to 35.6°C, the pack temperature difference reduced to 10.46°C, and the cell-level maximum temperature difference reduced to 6.9°C. This confirmed that side cooling leverages the higher in-plane thermal conductivity of the cell and offers a much larger heat transfer area than bottom cooling.
However, the temperature distribution of the side-cooled pack still revealed an obvious temperature gradient from the inlet side to the outlet side. To overcome this difficulty, I proposed a staggered inlet/outlet layout for the side-mounted plates. I compared the original same-side inlet/outlet configuration with a staggered configuration in which the inlet and outlet are on opposite ends of the plate. Under the same 2C discharge condition, the staggered side-mounted design reduced the maximum pack temperature from 35.6°C to 34.5°C, lowered the pack-level maximum temperature difference from 10.46°C to 8.5°C, while the cell-level maximum temperature difference remained essentially unchanged at approximately 6.9°C. The staggered pathway promotes more uniform coolant temperature rise along the plate and moderates hot-spot formation near the outlet. For this reason, I selected the side-mounted, stagger-inlet/outlet accordion plate as my baseline reference design for subsequent enhancement through surface structures.
| Cooling strategy | Tmax pack (°C) | ΔT cell (°C) | ΔT pack (°C) |
|---|---|---|---|
| Bottom cooling plate | 39.67 | 12.15 | 13.27 |
| Side cooling plate | 35.6 | 6.9 | 10.46 |
| Side plate with staggered inlet/outlet | 34.5 | 6.93 | 8.5 |
Although the staggered side-mounted baseline plate satisfies the maximum temperature objective of 35°C, the temperature difference remains above the strict engineering target of 5°C. To further enhance the cooling performance, I applied passive heat-transfer-enhancement concepts — specifically micro convex ribs and concave grooves arranged periodically in the flow channel. A convex rib protrudes into the coolant flow and periodically interrupts the thermal boundary layer, whereas a concave groove provides a recessed cavity that increases the local heat transfer area with minimal additional friction loss. Based on this complementary idea, I designed multiple representative flow-channel geometries in which ribs and grooves are alternately placed along the coolant path. I first examined the influence of the shape of the ribs and grooves. I compared four cross-sectional shapes — circular, diamond, forward water-drop, and reverse water-drop — for both convex ribs and concave grooves. The coolant volume flow rate was fixed at 2.42 L/min, the rib-to-rib and groove-to-groove spacing at 25 mm, and the height or depth at 2 mm for both structures.
I extracted the maximum surface temperature, the surface temperature standard deviation, the pressure drop, the average Nusselt number, the friction factor, and the performance evaluation criterion (PEC) for every configuration. The PEC factor, defined relative to the baseline accordion plate, is:
$$\text{PEC} = \frac{\overline{Nu} / \overline{Nu}_0}{\left( f / f_0 \right)^{1/3}},$$
where the subscript 0 refers to the baseline smooth accordion channel, overline Nu is the average Nusselt number, and f is the Fanning friction factor. The average Nusselt number and friction factor are respectively:
$$\overline{Nu} = \frac{h_{\text{aver}} D_h}{\lambda_f},$$
$$f = \frac{\Delta p}{2 \rho_f \overline{u}^2 L / D_h},$$
in which \(D_h\) denotes the hydraulic diameter of the channel, \(\lambda_f\) the coolant thermal conductivity, \(\Delta p\) the pressure drop across the plate, \(\rho_f\) the density, \(\overline{u}\) the average coolant velocity, and L the channel length. All four rib shapes and all four groove shapes produced PEC values larger than unity, indicating that both strengthening approaches are effective relative to the baseline. Among all shapes, circular ribs and circular grooves always delivered the highest enhancement of the Nusselt number ratio. Circular ribs achieved about 1.59 times the Nusselt number of the baseline plate, whereas circular grooves increased the Nusselt number to about 1.44 times the baseline value. The pressure drop results clearly revealed the trade-off between ribs and grooves: every rib shape increased the pressure drop above the baseline plate, while every groove shape reduced the pressure drop below the baseline plate. In particular, circular ribs increased the friction factor ratio \(f/f_0\) to 1.22, while circular grooves decreased this ratio to about 0.78. Because the circular geometry provided the strongest heat-transfer enhancement, I selected circular ribs and circular grooves for all further studies.
I then analyzed the effect of the coolant volume flow rate on the performance of the circular rib and circular groove plate designs. I varied the flow rate from 1.21 to 3.62 L/min. Increasing the flow rate always reduced the maximum surface temperature. For the ribbed plate, the maximum temperature dropped from 35.15°C at 1.21 L/min to 30.2°C at 3.62 L/min; for the grooved plate, the value dropped from 35.32°C to 30.35°C. Increasing the flow also reduced the surface temperature standard deviation, improving uniformity. Nevertheless, the pressure drop increased steeply with increasing flow rate. The ribbed plate consistently exhibited the highest pressure drop: at the highest flow rate, the pressure drop of the circular-rib plate was about 28.5% higher than that of the circular-groove plate. I therefore set the baseline volume flow rate at 2.42 L/min because the temperature reduction tends to flatten beyond this value while the pumping penalty continues to grow rapidly.
| Flow rate (L/min) | Rib Tmax (°C) | Groove Tmax (°C) | Rib Δp (Pa) | Groove Δp (Pa) |
|---|---|---|---|---|
| 1.21 | 35.15 | 35.32 | 144.2 | 103.8 |
| 1.81 | 33.27 | 33.40 | 235.7 | 166.5 |
| 2.42 | 31.64 | 31.80 | 394.7 | 258.8 |
| 3.02 | 30.92 | 31.05 | 610.4 | 400.1 |
| 3.62 | 30.20 | 30.35 | 880.9 | 578.2 |
I next studied the spacing between consecutive circular ribs and grooves. The evaluated spacing values were 35 mm, 30 mm, and 25 mm. As the spacing narrowed from 35 mm to 25 mm, the maximum temperature of the ribbed plate decreased from 31.76°C to 31.64°C and that of the grooved plate also decreased. More ribs or grooves per unit length enhance thermal boundary-layer interruption and therefore improve heat transfer. The pressure drop of the ribbed plate increased with decreasing spacing, whereas the pressure drop of the grooved plate slightly decreased with decreasing spacing because the additional cavity volume provides more expansion space for the flow. The PEC for both structures consistently improved as the spacing was reduced. Thus, I chose 25 mm as the most favorable spacing for the high-voltage battery cooling plate.
After fixing the shape, flow rate, and spacing, I evaluated the influence of the circular feature size by changing the diameter from 6 mm to 10 mm. The maximum temperature of the ribbed plate declined as the diameter increased, whereas the temperature standard deviation tended to rise. Larger convex ribs disturb the flow more strongly and improve cooling near the inlet region, but they also create a more non-uniform local temperature pattern. The grooved plate displayed only a mild decrease in maximum temperature with an increasing diameter because the flow in the groove is largely stagnant and thus less effective at convective heat transport. The friction loss of the ribbed plate increased notably with diameter, whereas the grooved plate displayed a slow pressure drop reduction with larger diameter. The PEC value of both structures improved with increasing diameter: the heat-transfer gain outweighed the additional friction penalty for the ribbed design. I consequently selected 10 mm as the best diameter combining high PEC and good maximum-temperature control.
From the above single-factor studies, I proposed a spatially non-uniform design in which circular convex ribs and circular concave grooves alternate along the coolant flow direction in a staggered fashion. This rib-groove alternating configuration integrates the heat transfer enhancement of convex ribs and the friction-saving advantage of concave grooves. Before full design optimization, I carried out parametric studies to determine whether the height of the convex ribs and the depth of the concave grooves should be uniform or graded along the flow direction. A preliminary analysis showed that heat transfer demand is larger near the outlet because the coolant temperature is already elevated there. Better temperature uniformity could be achieved if the disturbance intensity is relatively mild near the inlet and becomes stronger near the outlet. This observation motivated me to adopt a monotonically increasing height and depth profile along the channel. I designated the first-column rib height as \( h_1 \), the last-column rib height as \( h_{19} \), the first-column groove depth as \( d_1 \), and the last-column groove depth as \( d_{18} \). All intermediate columns vary linearly between these two end values. For 19 rib columns and 18 groove columns, the linear increments are:
$$\delta = \frac{h_{19} – h_1}{18},$$
$$\varepsilon = \frac{d_{18} – d_1}{17},$$
$$h_i = h_1 + \left( i – 1 \right) \delta ,\quad i = 1,2,\dots ,19,$$
$$d_j = d_1 + \left( j – 1 \right) \varepsilon ,\quad j = 1,2,\dots ,18.$$
Here \(h_i\) denotes the height of the \(i\)-th convex rib column and \(d_j\) represents the depth of the \(j\)-th concave groove column. The design variables for multi-objective optimization were therefore \(h_1\), \(h_{19}\), \(d_1\), and \(d_{18}\). Their valid ranges are shown in the table below. The lower bound of 0 mm corresponds to the baseline smooth channel, while the upper bound of 2 mm corresponds to the maximum structure height/depth compatible with the 4-mm channel depth without excessively blocking the passage.
| Variable | Geometric parameter | Lower bound (mm) | Upper bound (mm) |
|---|---|---|---|
| \(x_1\) | First rib height \(h_1\) | 0 | 2 |
| \(x_2\) | Last rib height \(h_{19}\) | 0 | 2 |
| \(x_3\) | First groove depth \(d_1\) | −2 | 0 |
| \(x_4\) | Last groove depth \(d_{18}\) | −2 | 0 |
I employed the optimal Latin hypercube design method to sample 84 configurations across this four-dimensional design space. For each sample, I constructed the three-dimensional water channel geometry, generated the computational mesh, and performed a conjugate heat transfer simulation. The heat source was a 2C discharge from a pair of cells adjacent to the plate. The coolant inlet temperature was set to 25°C and the volume flow rate through each plate was fixed at 2.42 L/min. For every simulation, I extracted three performance objectives:
- \(T_{\max}\): maximum temperature of the plate surface in degrees Celsius, which directly correlates with the peak temperature in the high-voltage battery cells.
- \(T_{\text{sd}}\): standard deviation of the plate surface temperature, representing the temperature uniformity of the cooling surface.
- \(\Delta p\): pressure drop from the inlet to the outlet of the plate, representing the pumping power consumption.
A representative set of the sampled design points and their corresponding simulated responses is given in the table below. The four design variables are normalized within their physical ranges.
| Sample | \(h_1\) (mm) | \(h_{19}\) (mm) | \(d_1\) (mm) | \(d_{18}\) (mm) | \(T_{\max}\) (°C) | \(T_{\text{sd}}\) (°C) | \(\Delta p\) (Pa) |
|---|---|---|---|---|---|---|---|
| 1 | 0.3 | 0.9 | −1.7 | −1.8 | 35.857 | 1.278 | 262.3 |
| 2 | 0.8 | 0.3 | −0.4 | −0.2 | 35.915 | 1.298 | 259.5 |
| 3 | 2.0 | 1.4 | −1.3 | −1.0 | 35.847 | 1.325 | 305.8 |
| 4 | 1.2 | 1.8 | −1.5 | −1.7 | 35.798 | 1.305 | 294.7 |
| 5 | 0.1 | 0.5 | −0.6 | −1.1 | 35.886 | 1.276 | 255.4 |
| 6 | 0.9 | 0.0 | −1.2 | −1.6 | 36.010 | 1.304 | 259.6 |
| 7 | 0.5 | 1.2 | −0.5 | −2.0 | 35.814 | 1.272 | 267.8 |
| 8 | 1.7 | 0.8 | −0.9 | −1.9 | 35.915 | 1.320 | 282.1 |
| 9 | 1.8 | 1.1 | −0.2 | −0.3 | 35.880 | 1.310 | 289.2 |
| 10 | 0.0 | 1.0 | −1.8 | −0.7 | 35.827 | 1.273 | 259.5 |
For efficient optimization, I selected the radial basis function surrogate model to approximate the expensive CFD responses. The RBF model is particularly suitable for this multi-dimensional design problem because it offers high flexibility for nonlinearity while maintaining reasonable computational cost. I selected a Gaussian basis function and used the 84 design points to construct three separate surrogate models — one for each performance response. After model construction, I calculated the coefficient of determination \(R^2\) between the surrogate predictions and the CFD simulation results for verification. The \(R^2\) values for the maximum temperature, temperature standard deviation, and pressure drop were 0.9009, 0.9291, and 0.9624, respectively. All three coefficients exceeded the 0.9 threshold, confirming that the surrogate model accurately represented the underlying CFD responses within the design space.
Using these surrogate models, I performed multi-objective optimization with the non-dominated sorting genetic algorithm II (NSGA-II). The objective functions for the mathematical optimization problem can be expressed as:
$$\text{Find} \quad x = \left[ x_1, x_2, x_3, x_4 \right] = \left[ h_1, h_{19}, d_1, d_{18} \right],$$
$$\text{Minimize} \quad F\left( x \right) = \left[ T_{\max}\left( x \right),\quad T_{\text{sd}}\left( x \right),\quad \Delta p\left( x \right) \right],$$
$$\text{subject to} \quad \Delta p\left( x \right) < \Delta p_0 ,$$
where \(\Delta p_0\) refers to the pressure drop of the baseline staggered side-mounted accordion plate. The NSGA-II parameters were set as a population size of 20, 100 generations, a crossover probability of 0.8, and a mutation probability of 0.1. After the optimization process, I obtained the Pareto front linking maximum temperature, temperature standard deviation, and pressure drop. I selected the final optimum from the front by giving priority to low maximum temperature and low pressure drop: the selected Pareto point corresponded to a maximum plate surface temperature of 31.726°C, a temperature standard deviation of 1.258°C, and a pressure drop of 276.7 Pa. The corresponding design parameters were approximately \(h_1 = 0\) mm, \(h_{19} = 2\) mm, \(d_1 = -0.82\) mm, and \(d_{18} = -2\) mm. After rounding these values to practical manufacturing precision, the optimal parameters became \(h_1 = 0\) mm, \(h_{19} = 2\) mm, \(d_1 = -0.8\) mm, and \(d_{18} = -2\) mm. The convex rib height thus increases progressively along the coolant direction, while the concave groove depth also increases progressively along the plate.
| Design | \(h_1\) (mm) | \(h_{19}\) (mm) | \(d_1\) (mm) | \(d_{18}\) (mm) | \(T_{\max}\) (°C) | \(T_{\text{sd}}\) (°C) | \(\Delta p\) (Pa) |
|---|---|---|---|---|---|---|---|
| Rounded optimum design | 0 | 2 | −0.8 | −2 | 31.712 | 1.261 | 273.4 |
| Original accordion plate | — | — | — | — | 32.710 | — | 300.4 |
After rounding the optimized design parameters, I ran a final CFD simulation on the improved liquid cooling plate. The simulation confirmed that the maximum surface temperature was reduced to 31.712°C with a pressure drop of 273.4 Pa, closely matching the surrogate model prediction. I then assembled the optimized staggered rib-groove plate into the complete high-voltage battery pack model and simulated a 2C constant-current discharge with the same boundary conditions as before. The pack-level results are shown in the table below. Compared with the original side-mounted accordion plate, the optimized rib-groove plate lowered the maximum pack temperature from 34.5°C to 33.46°C — a 3% improvement. The maximum cell temperature difference dropped by 10.1%, and the pack-level temperature difference decreased by 8.94% from 8.5°C to 7.74°C. Even more significantly, the pressure drop across the cooling system was reduced by 8.99% from 2703.6 Pa to 2460.6 Pa. This indicates that the staggered rib-groove structure enhanced the heat transfer and improved the temperature uniformity while simultaneously reducing the pumping energy requirement relative to the baseline accordion plate.
| Configration | \(T_{\max,\text{pack}}\) (°C) | \(\Delta T_{\max,\text{cell}}\) (°C) | \(\Delta T_{\max,\text{pack}}\) (°C) | \(\Delta p\) (Pa) |
|---|---|---|---|---|
| Optimized staggered rib-groove plate | 33.46 | 6.23 | 7.74 | 2460.6 |
| Baseline side-mounted accordion plate | 34.5 | 6.93 | 8.5 | 2703.6 |
| Improvement | −3% | −10.1% | −8.94% | −8.99% |
To demonstrate that the optimized rib-groove cooling plate meets practical engineering requirements, I evaluated the battery pack thermal management system under three representative operating scenarios. The first scenario is fast charging, which is one of the most demanding thermal conditions for a high-voltage battery because the vehicle is stationary and the waste heat from the battery must be rejected solely by the liquid cooling system. In this simulation I used a stepped charging strategy: the high-voltage battery was charged at 2C from 0% to 60% state-of-charge, then at 1C from 60% to 90%, and finally at 0.5C from 90% to 100%. The total charging time was 2880 s (about 48 minutes), and the pack reached 80% state-of-charge in 30 minutes, consistent with current fast-charging capability for electric vehicles. The ambient and initial battery temperature was 25°C, the coolant inlet temperature was 25°C, and the coolant volume flow rate was set to 21.78 L/min for the whole pack. During the 2C phase, the maximum pack temperature rose to 30.13°C at the end of the 2C segment, with a pack temperature difference of 4.53°C. After the current tapered to the 1C and 0.5C phases, the temperature decreased steadily. At the end of charging, the maximum pack temperature was 26.45°C and the temperature difference was only 1.3°C. Throughout the entire fast-charging process, the maximum temperature remained below 30.5°C — far below the 35°C design target of the high-voltage battery system — and the maximum temperature difference never exceeded 5°C.
The second scenario I evaluated was low-temperature heating. When a high-voltage battery is exposed to freezing temperatures, its internal resistance rises sharply and lithium plating becomes possible during charging. Therefore, the battery pack must be preheated before charging in cold weather. I initialized the battery cells, thermal pads, and cooling plates to −20°C. Warm coolant at 15°C was supplied through the same plates to heat the pack from the outside inward. In this configuration, the heat is transferred from the coolant to the plate, then through the thermal pad into the cells. The criterion for allowing charging is that the minimum cell temperature must reach 0°C, while heating continues until the minimum cell temperature exceeds 10°C. Simulation results showed that the minimum pack temperature rose above 0°C after approximately 620 s of heating, at which point the cells were permitted to accept a low charging current. The pack reached a minimum temperature of 10.23°C after about 1210 s, at which point the heating was switched off. In this final state, the maximum temperature was 15.03°C and the minimum temperature was 10.23°C, resulting in a maximum in-pack temperature difference of 4.8°C. The average heating rate over the entire operation was approximately 1.5°C/min, which is much greater than the engineering requirement of 0.3°C/min. These results confirm that the optimized rib-groove plate can also operate effectively in reverse mode as a heating plate for cold-weather charging of the high-voltage battery.
| Indicator | Value |
|---|---|
| Time to reach >0°C minimum cell temperature | 620 s |
| Time to reach >10°C minimum cell temperature | 1210 s |
| Minimum cell temperature at heat stop | 10.23°C |
| Maximum cell temperature at heat stop | 15.03°C |
| Average heating rate | about 1.5°C/min |
| Maximum temperature difference at heat stop | 4.8°C |
The third scenario was a high-temperature highway cruise condition. This scenario simulates the battery pack starting at 40°C after prolonged parking in the summer sun, followed by a 120 km/h highway cruise. Under this condition, the battery controller must reject both the ambient heat soak and the internally generated heat during discharge. I calculated the motor power requirement using the vehicle road-load equation:
$$P = \frac{1}{\eta_t} \left( \frac{G f_r u_a}{3600} + \frac{C_D A u_a^3}{76140} \right),$$
where \(G\) is the vehicle weight, \(f_r\) the rolling resistance coefficient, \(C_D\) the aerodynamic drag coefficient, \(A\) the frontal area, \(u_a\) the vehicle speed, and \(\eta_t\) the drivetrain efficiency. Inserting the parameters of an electric off-road vehicle (mass 3293 kg, drag coefficient 0.6, frontal area 3 m², rolling resistance 0.018, and drivetrain efficiency 0.93), the power requirement at 120 km/h was approximately 65 kW. Considering that the pack consists of two parallel branches, this corresponds to roughly a 0.5C discharge rate per cell. In the simulation, I set the initial cell temperature and ambient temperature to 40°C and the coolant inlet temperature to 25°C. The results showed that the maximum pack temperature dropped rapidly from 40°C at the beginning of the cruise. After about 390 s, the maximum temperature fell below 35°C, satisfying the recommended upper limit of the high-voltage battery. After approximately 770 s of cruising, the pack temperature difference fell below 5°C. As the system approached thermal equilibrium, the maximum pack temperature stabilized at about 25.77°C and the maximum in-pack temperature difference stabilized at about 0.66°C. The rib-groove liquid cooling system therefore proved capable of quickly controlling a hot-soaked high-voltage battery during highway operation while simultaneously providing excellent temperature uniformity across the pack.
| Indicator | Value |
|---|---|
| Maximum temperature after 390 s | < 35°C |
| Time to reduce temperature difference below 5°C | 770 s |
| Stabilized maximum pack temperature | 25.77°C |
| Stabilized maximum temperature difference | 0.66°C |
Across all three representative operating conditions, the optimized staggered rib-groove cooling plate fulfilled the thermal management requirements of the high-voltage battery system. During fast charging, the maximum temperature remained below 31°C and the temperature difference below 5°C for the entire charging profile. During cold-weather preconditioning, the plate warmed the pack from −20°C to above 10°C at a rapid average rate of about 1.5°C/min, enabling fast charging without lithium-plating risks. During the most severe hot-ambient highway cruise, the cooling system rapidly drew the pack temperature down to below 35°C within 6.5 minutes and eventually stabilized the entire high-voltage battery pack at under 26°C with a temperature spread below 1°C. These results confirm the robustness and versatility of the proposed rib-groove liquid cooling structure over a broad range of electrochemical and environmental conditions.
In summary, my work delivers a systematic method to improve the liquid cooling performance of a high-voltage battery pack. The main design path includes three stages: first, selecting a side-mounted liquid cooling architecture with staggered inlet and outlet ports to exploit the favorable thermal conduction path of the cell and reduce the longitudinal temperature gradient; second, introducing circular convex ribs and circular concave grooves alternately along the flow channel, with the geometric spacing and diameter tuned through single-factor studies; and finally, applying the RBF surrogate model with NSGA-II multi-objective optimization to optimize the rib height and groove depth profiles along the flow direction. The resulting cooling plate lowers the maximum temperature of the high-voltage battery pack by 3% while reducing the pack temperature difference by 8.94% and decreasing the pressure drop by 8.99% relative to a conventional side-mounted accordion plate. These improvements are achieved without any additional pumping power; in fact, the optimized design is more energy-efficient than the conventional design, which is beneficial for the energy economy of electric vehicles.
Despite these promising findings, the present study has several limitations. First, my simulation ignored the detailed internal structure of the lithium-ion cells and treated them as homogeneous anisotropic heat-generating solids. Although this is a standard engineering approximation accepted in the literature, more accurate cell-resolved models or electro-thermal coupled models could refine the local temperature prediction near the tabs and the jelly-roll surfaces. Second, I only validated the single-cell temperature rise against experimental data. The complete liquid cooling plate performance was verified through numerical simulation alone. Experimental validation of the optimized rib-groove cooling plate on a pack-level test bench should be conducted in future research. Third, the inlet coolant temperature was treated as constant in my simulations. In an actual vehicle, the coolant temperature entering the pack varies over time because of the thermal inertia of the entire vehicle thermal management loop. In future work, a coupled system-level thermal simulation with a realistic heat-exchanger model should be explored. Fourth, I limited the geometric optimization to the height and depth profiles of the rib and groove arrays. Other parameters such as the spacing, diameter, and pitch may interact with the optimized height profile. A more comprehensive design optimization that includes these parameters simultaneously may yield further improvement, although it will require more computational resources. Finally, the long-term cycling behavior and aging of the high-voltage battery with the optimized cooling plate under repeated fast charging and discharging should be evaluated experimentally to assess durability. Nevertheless, the results of this work indicate that staggered rib-groove structures are an effective heat-transfer enhancement method for prismatic high-voltage battery cooling plates, providing better performance than the conventional smooth accordion channel at a lower pressure drop. The proposed design therefore offers a valuable improvement for the thermal management of prismatic high-voltage battery packs in new energy vehicles.